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The impact of surge pricing on customer retention
Abstract
This study explores how satisfied customers are when they face surge pricing as well as how customer satisfaction affects customer retention. This study uses fuzzy set/Qualitative Comparative Analysis to generate relations and then qualitative analysis with structural associations to propagate the values and refine these relations. Both methods together generate proper relations for multi-layered problems. With data gathered from a group of executive MBA students in Taiwan, the empirical results show that loyal riders are more tolerable to surge pricing than non-loyal riders. Lastly, the evidence presents that customer satisfaction does not always positively affect customer retention.
... Additionally, many scholars have discussed the possible impact of operations on CR (Ahmad & Buttle, 2002; 155 Huarng & Yu, 2020; Kanwal & Rajput, 2014;Ray & Chiagouris, 2009) in the retail industry in recent years. While the main remains just partially reflect an operational prerequisite role in delivering perceived benefits for customer satisfaction or loyalty and retention (Aparna et al., 2018;Blut et al., 2018;Bojei et al., 2013;Hanaysha, 2018;Huarng & Yu, 2020;Julian et al., 2015;Sharmeela-Banu et al., 2012). ...
... Remarkably, these research findings are consistent with that of Mazumdar (1993), who claims that consumers often purchase based on their careful consideration of what benefits they obtain". Moreover, these results reflect the concepts of Ahmad and Buttle (2002), Bojei et al. (2013), Huarng and Yu (2020), Ray and Chiagouris (2009), Kanwal andRajput (2014), andSharmeela-Banu et al. (2012), who argue that operational factors may influence CR in retailing. Although the research 450 findings seem consistent with previous studies, which found that customers can gain benefits when shopping in physical stores, it is based primarily on an operations perspective to discuss the dimensions of PB and the relationship of PB and CR in an omnichannel retailing context. ...
In a world with enormous opportunities and challenges from the 4.0 revolution and the lingering COVID-19 pandemic, customer retention is more important than ever for retailers. While marketing and advertising can be more or less limited during the pandemic, retailers pay more attention to the supply and service operations of products as salvage to satisfy the essential demands of customers. However, few scholars discuss the effects of service operations on customer retention in retail because it is lower consumer awareness and challenging to measure accurately and adequately. Therefore, with the foundation of commitment-trust theory, this study examines service operations’ direct and indirect effects on customer retention through perceived benefit in omnichannel retailers. Simultaneously, it assesses how psychological ownership affects customer retention and moderates the effect of perceived benefit on customer retention in the Vietnamese supermarket as empirical evidence. The combination of a qualitative method (with 32 in-depth interviews) and a quantitative method (through a survey conducted with 374 shoppers) is implemented. Partial least-squares structural equation modelling with SmartPLS software is utilized for data analysis and hypothesis testing. From the findings, the study offers an operations perspective and a customer view of how to store service operations contribute to customer perception of benefits and customer retention. Interestingly, the study discovered that psychological ownership is not only a critical antecedent of customer retention but also enhances the effect of perceived benefit on customer retention as its moderating role.
... For instance, Thai and Wang (2020) and Wang et al. (2021) employed fsQCA to examine the structural associations of social endorsement and customer-brand relationship. Huarng and Yu (2020) applied the technique to explore the impact of surge pricing and customer loyalty on satisfaction, thereby leading to customer retention in ride-sharing services. Therefore, we applied fsQCA to investigate whether the interconnections of technological factors (model 1), health factors (model 2) and their combinations (model 3) sufficiently lead to intention, then actual use (Figure 2). ...
... Second, the relations between one layer to the next were screened based on two criteria: consistency (CO) (Equation 2) ≥ 0.7 and the number of cases (#) ≥ 10 (Huarng and Yu, 2020). Third, sufficient condition between variables of one layer to the subsequent was determined by NC value, i.e. values between 0.0 and 0.44 are negative, between 0.45 and 0.55 are neutral and between 0.56 and 1.0 are positive (Huarng and Yu, 2020). For instance, 0.30 and 0.60 of intention are interpreted as negative and positive adoption intention, respectively. ...
Purpose
During the challenging time of lockdown and isolation due to the coronavirus disease (COVID-19), contact-tracing apps have played a critical role in health communication and preventive healthcare. This study proposed and tested an extended technology acceptance model (TAM) with key health factors (i.e. health risk perception from COVID-19, health information orientation to COVID-19 and health consciousness) to understand individuals' adoption of COVID-19 contact-tracing apps.
Design/methodology/approach
A two-stage online survey was conducted to collect data on US individuals’ intention and actual use of COVID-19 contact-tracing apps. The sample comprises 288 valid responses. Partial least squares structural equation modeling (PLS-SEM) and fuzzy set/qualitative comparative analysis (fsQCA) were employed as the complementary approaches.
Findings
The findings from PLS-SEM revealed that health risk perception, health information orientation and perceived usefulness have positive net effects on behavioral intention, which, in turn, affects actual use. The results from fsQCA highlighted the explanatory power of the extended TAM to COVID-19 contact-tracing app adoption.
Originality/value
Although TAM is considerably effective in measuring technology acceptance, the phenomenon is highly context-driven. How technological and health factors simultaneously motivate the use of contact-tracing apps has not been well documented. The present study offers some implications for practitioners concerned about fostering the adoption of mobile health services in the time of COVID-19. Methodologically, this study is among the first to blend PLS-SEM and fsQCA to measure the explanatory power of a structural model.
... The competitive nature of the freight transport markets often dictates pricing, with variations based on direction, season, and service quality. To remain viable, overall prices must cover operational costs [5]. The interplay between transport demand and supply is complex, where transport supply can exist without an immediate corresponding demand, but demand cannot occur without an adequate supply [6]. ...
Commuters' mobility plays significant roles in urban economic due to its reliance on the cheapest means and available transportation system from one location to another. Commuters' income in Lagos State affects the amount of traffic generated along the waterways during travel behavior due to commuters' occupation and commuters' level of car ownership. This study aims to estimate the impact of ferry commuters' income on the waterways operations in Lagos state. This survey was carried out in the four selected waterways terminals in Lagos State. The authors used primary data with the aid of snow balling sampling technique to administered 836 questionnaires at the selected inland waterways terminals in Lagos State. The study used multiple regressions to analyze the obtained data in the study area. The result of the findings revealed that larger proportion of the respondents representing 63.9% (523) of the sample size had no car. Also, passenger's income that was measured using passengers' occupation and passengers' car ownership had a significant impact on ferry operational costs in Lagos State having R value of .699 (69.9%) and p-value of 0.000. This shows that ferry operational costs can be determined by passengers' daily or monthly income. 2 The study concluded that ferry operating costs tend to be lower when the level of patronage is minimal due to commuters' income constraints. It was recommended that government should subsidize the freight price and come up with a policy that will enforce usage of ferry service.
... The competitive nature of the freight transport markets often dictates pricing, with variations based on direction, season, and service quality. To remain viable, overall prices must cover operational costs [5]. The interplay between transport demand and supply is complex, where transport supply can exist without an immediate corresponding demand, but demand cannot occur without an adequate supply [6]. ...
Commuters’ mobility plays significant roles in urban economic due to its reliance on the cheapest means and available transportation system from one location to another. Commuters’ income in Lagos State affects the number of traffic generated along waterways during travel behavior such as commuters’ occupation and commuters’ level of car ownership. This study aims to estimate the impact of commuters’ income on the ferry operations in Lagos state. The research was carried out in four selected waterways terminals in Lagos State. The authors used primary data with the aid of snow balling sampling technique to administered 836 questionnaires at the selected inland waterways terminals in Lagos State. The study used multiple regressions to analyze the obtained data in the study area. The result of the findings revealed that majority of the respondents representing 63.9% (523) of the sample size had no car. Furthermore, passenger’s income that was measured using passengers’ occupation and passengers’ car ownership had a significant impact on ferry operational costs in Lagos State having R value of .699 (69.9%) and p-value of 0.000. This shows that ferry operational costs can be determined by passengers’ daily or monthly income. The study concluded that increase in mobility demand along waterways can be experienced when traveling cost is minimal compared to other means of transportation. It was recommended that government should subsidize the freight price and come up with a policy that will enforce usage of ferry service.
... Hence, industrial and academic researchers have increased investigations on the competitive pricing problem in recent decades. (Li et al. 2019;Huarng and Yu 2020;Hermel et al. 2021;Button 2022). ...
This study explores how manufacturers in the competitive supply chain can set prices and secure funding effectively. We use game theory to look at how competition between domestic and foreign manufacturers affects pricing decisions. Our research investigates how a domestic manufacturer can improve its market share by addressing financial challenges through modern financing methods. In this scenario, a domestic manufacturer competes with a foreign one to attract a retailer's market share and profits. The retailer decides what products to buy and how to price them based on bid prices and demand. We also consider that the domestic manufacturer will use online crowdfunding platforms to tackle its financial problem. Hence, our study sets up a supply chain where competition revolves around both operational and financial decisions. Mathematical models are developed to analyze how costs, finances, market potential, and price sensitivity impact various parts of the supply chain. The results reveal that decisions made on the crowdfunding platform significantly influence other supply chain decisions. Manufacturers and retailers need to pay attention to the financial decisions made on this platform to maximize profits. Also, domestic and foreign manufacturers should consider customer preferences for their products when setting prices. Finally, the results demonstrate that a domestic manufacturer can gain a competitive edge in the retail market by carefully considering both product pricing and financial decisions, including those made on the lending platform.
... Consumers manifest protective behaviors toward particular products, either driven by price considerations or established brand recognition (Huarng & Yu, 2020)). Consequently, customer retention emerges as a process that fosters loyalty through the cultivation of robust customer relationships (Amanah et al., 2021;Han et al., 2019). ...
Grounded in the Push-Pull-Mooring (PPM) theory of migration, this study employs the PPM model as a pivotal framework to investigate the dynamics of omnichannel retailing. The primary aim is to advance our understanding of omnichannel strategies and their role in fostering a strong customer base to promote customer retention. This research explores the autonomous components of omnichannel, with specific emphasis on the intervening factor of Pull, which is represented by the concept of "Retailer's Identity Attractiveness." The findings of this study highlight a positive correlation between omnichannel practices and customer retention, emphasizing how systematic employment of omnichannel strategies can lead to increased sales profitability and enriched shopping experiences. Furthermore, our investigation reveals that "Retailer's Identity Attractiveness" acts as a mediator, offering partial insights into the impact of omnichannel strategies on customer retention. In summary, this research illuminates how retailers can harness omnichannel approaches and the appeal of their identity to proficiently sustain and expand their customer base.
... In addition, studies have found that user satisfaction and loyalty are crucial for user retention [8], and the retention behavior of loyal users has a positive effect on traditional platforms for transformation and upgrading [10]. However, user satisfaction studies have reported controversial findings; some argue that satisfaction is the primary determinant of customer retention [11,12], but others propose a different or even the opposite view, arguing that satisfaction does not always positively affect customer retention [13] and that the relationship between the two is relatively weak [14]. ...
To achieve user retention through multifactor synergy, Internet enterprises must reduce costs and increase efficiency and sustainable development. In response to the dilemma that Internet companies are experiencing increasingly high user acquisition costs and serious user churn, this paper investigates a sample of 46,695 user reviews of nine product series from Xiaomi Ecological Chain. Case studies and qualitative comparative analysis are used to explore the influence mechanisms of quality of experience, brand trust, and brand attachment on users’ retention intentions. Our findings are as follows. (1) Brand attachment alone is not necessary for high user retention intention, but user perception, cognition, and brand trust are necessary. (2) Quality of experience positively impacts brand trust, attachment, and user retention intention. Therefore, improving user perception and cognition is critical in generating high user retention intention. (3) Five configuration paths can achieve high user retention intention, while three configuration paths lead to low user retention intention, and there is an asymmetric relationship between these paths. Among them, the role of quality of experience-driven configuration paths in generating user retention intention is the most prominent. (4) User perception and cognition can substitute with brand trust and attachment in the substitution relationship between configuration paths. Our findings have important theoretical and practical implications for revealing the realization paths of high user retention intention in Internet companies and provide a new perspective for future research.
... In addition, studies have found that user satisfaction and loyalty are crucial for user retention [8], and the retention behavior of loyal users has a positive effect on traditional platforms for transformation and upgrading [10]. However, user satisfaction studies have reported controversial findings; some argue that satisfaction is the primary determinant of customer retention [11,12], but others propose a different or even opposite view, arguing that satisfaction does not always positively affect customer retention [13]and that the relationship between the two is relatively weak [14]. ...
To achieve user retention through multifactor synergy, Internet enterprises must reduce costs and increase efficiency and sustainable development. In response to the dilemma that Internet compa-nies are experiencing increasingly high user acquisition costs and serious user churn, this paper uses a sample of 46,695 user reviews of nine product series from Xiaomi Ecological Chain. Case studies and qualitative comparative analysis are used to explore the influence mechanisms of quality of experience, brand trust, and brand attachment on users' retention intentions. Our find-ings are as follows. (1) Brand attachment alone is not necessary for high user retention intention, but user perception, cognition, and brand trust are necessary. (2) Quality of experience positively impacts brand trust, attachment, and user retention intention. Therefore, improving user perception and cognition is critical in generating high user retention intention. (3) Five configuration paths can achieve high user retention intention, three configuration paths lead to low user retention intention, and there is an asymmetric relationship between these paths. Among them, the role of quality of experience-driven configuration paths in generating user retention intention is the most prominent. (4) In the substitution relationship between configuration paths, user perception, and cognition can substitute with brand trust and attachment. Our findings have important theoretical and practical implications for revealing the realization paths of high user retention intention in Internet companies and provide a new perspective for future research.
... Unlike other qualitative comparative analyses, fs/QCA can handle the problems of degree change or partial membership. For this reason, fs/QCA has been widely used in relevant empirical studies in recent years, employing the method to explain the public policy for innovative governance [41], to analyze the impact of surge pricing on customer retention [42], and to identify the configurations in the relationship between environmental practices and other management practices to improve labor productivity [43]. This study employed fs/QCA to analyze the multi-level and linkage matching impact on CHI technology promotion based on the TOE framework. ...
With the nation's remarkable improvement in living standards, China's health insurance system cannot satisfy people's higher demands; therefore, it is necessary to promote the supply of commercial health insurance (CHI) in China. Based on the technology–organization–environment (TOE) framework, this study constructs a novel analysis framework to investigate the driving path of China's CHI. Employing the data of 31 provincial regions of China in 2018, a fuzzy-set qualitative comparative analysis is conducted to analyze configurations. We also adopt a necessary condition analysis in the robustness check to examine the necessary conditions, determining that no necessary relationship exists between possible conditions and the performance of CHI. More particularly, three sufficient configurations, TOE strategy, government attention (GA)–environment adaptability (EA)–citizen demand (CD) strategy, and dual EA–CD strategy are demonstrated to achieve high performance, and the other three configurations of technological management capability (TMC)–EA-CD strategy, technological infrastructure (TI)–EA strategy, and combined TI–TMC–EA strategy do not result in high performance. In addition, technological conditions (TI and TMC) and EA are relatively more important than the other configurations. Notably, government departments' financial expenditure is found to have a negative effect on CHI promotion.
... Customer retention is a link between customer loyalty and profitability, which is a form of loyalty related to consumer buying behavior as indicated by the high frequency of a consumer buying a product/service. Customers behave to defend certain brands, either because of price or brand image (Huarng and Yu, 2020). Heesup, Shim, Lee, and Kim (2019) defined customer retention as the process of creating loyalty by fostering good relationships with customers. ...
... DP Hai employed the method to explain the public policy for innovative governance [32]. KH Huarng and THK Yu analyzed the impact of surge pricing on customer retention by the method [33]. C Llopis-Albert, JM Merigo, YJ Xu and HC Liao analyzed the level of satisfaction of stakeholders in the public participation process of water resources management, which is mandatory according to the EU Water Framework Directive [34]. ...
Background
With the improvement in the living standards, China’s health insurance under the social security system cannot satisfy people's diversified and high-level demands. Therefore, it is necessary to promote commercial health insurance (CHI). This study identifies driving paths of CHI in China from configuration perspective.
Methods
This study innovatively constructs an analysis framework based on the Technology-Organization-Environment theory to investigate the driving path of China's commercial health insurance. Using the data of 31 provincial regions of China in 2018, the fuzzy-set Qualitative Comparative Analysis (QCA) is employed for configuration analysis. For the robustness analysis of necessary condition, we also adopt the Necessary Condition Analysis.
Results
Three main findings are discovered. First, there is no necessary relationship between any condition and high or not-high performance of CHI and any condition. Nevertheless, there are three sufficient configurations, TOE strategy, GA-EA-CD strategy, and dual EA-CD strategy, to achieve high performance, and another three, TMC-EA-CD strategy, TI-EA strategy, and TI-TMC-EA strategy, to reach not-high performance. Second, technological conditions (TI and TMC) and EA are relatively more important than other conditions. Third, it is confirmed that the financial expenditure of government departments has a negative effect on the development of commercial health insurance.
Conclusion
There are configurations or pathways to achieve high or not-high performance of promoting CHI and key factors are identified successfully. Each region should choose the driving path suitable for itself, instead of making homogenization policies and replicating policies of regions with high performance. Besides, TC and EA as key factors should be overcome. Finally, the governments should formulate policies to systematically evaluate social insurance and CHI simultaneously and promote their coordinated development.
Purpose
This paper aims to provide a conceptual understanding of the drivers and outcomes of actor opportunism in the context of the three key actors of the sharing economy – the service provider, the platform and the consumer.
Design/methodology/approach
The research uses a conceptual approach by drawing on literature from within and outside of marketing.
Findings
The current research introduces a conceptual framework of opportunism in the sharing economy with seven underlying propositions. The framework posits a U-shaped moderating effect of social capital for the relationship between opportunism and its drivers, actor vulnerability and asset specificity. Furthermore, a 2 × 2 matrix consisting of two types of opportunistic behaviors (active and passive) and two coping strategies by other actors (defensive and nondefensive) suggests that passive opportunism tends to lead to value codestruction independently of the coping strategies employed by other actors. Counterintuitively, the combination of active opportunism and defensive coping strategy presents an opportunity for value cocreation due to its potential to break up older structures and generate new ones.
Research limitations/implications
While our research provides a higher-level understanding of opportunism pertaining to platform, consumers and service providers in the sharing economy, future research could situate our framework within specific regulatory environments, incorporate the role of competitors and examine individual interaction effects between type of opportunism and coping strategies.
Practical implications
The framework enables service providers, platforms and consumers to identify drivers of opportunistic behaviors of their partners and discern instances in which opportunistic behaviors lead to value codestruction for all actors.
Originality/value
This research transcends prior work on the bright and dark sides of the sharing economy by identifying its dynamic nature and examining the contributing role of opportunism.
In the hospitality industry, repeat customers are recognized for their significant contributions, not just because they visit a business again but also because they generate strong word-of-mouth impacts on potential customers’ decisions. However, the quality of repeat customers’ word-of-mouth should be reconsidered for its pivotal role in influencing new customers. This research examines the effectiveness of repeat customers’ word-of-mouth compared to first-time customers. Employing a multi-study, multi-method approach, the study examines whether the quality and usefulness of online reviews written by repeat customers is indeed superior to those of first-time customers, through text analysis (Study 1), an experiment (Study 2), and a regression analysis utilizing secondary data (Study 3). Contrary to common belief, the results of the three studies reveal that repeat customers’ reviews do not surpass those of first-time customers in terms of quality, usefulness, or attracting new customers, highlighting the importance of considering quality when assessing customers’ indirect contributions.
This research aims to explore market mavericks by redefining sales velocity and profit surge in today’s dynamic business environment in emerging economies. The study focuses on the interplay between Sales Excellence (SE), Sales Capability (SC), Market Alignment (MA), Strategic Responsiveness (SR), and Dynamic Sales Management (DSM). Data from 180 companies (2021–2023), provided by financial leaders, were analyzed using SPSS (23.0) and AMOS (23.0) software. The analysis employed exploratory factor analysis (EFA), reliability analysis, and confirmatory factor analysis (CFA). The results highlight the critical role of these factors in shaping market mavericks and their significant impact on sales and profits in emerging economies. Specifically, SE enhances sales and profits when supported by effective strategies, SC drives organizational change by aligning service quality with SE, and MA drives sales velocity and profit surges through accurate forecasting. SR positively influences sales results by aligning sales with corporate strategy, while DSM is critical for motivating salespeople and shows strong links to SC and SR for successful adaptation in a dynamic business environment. The study reveals the interdependence of these factors and emphasizes the need for seamless integration and coordination to drive effective organizational change. These findings have significant implications for corporations seeking to improve their sales strategies and achieve sustainable growth in a rapidly evolving marketplace in emerging economies. This research explores market mavericks, redefines sales velocity and profit surge, and provides valuable insights into the critical factors shaping market mavericks and their impact on sales and profits. It offers guidance for organizations seeking sustainable growth.
Dynamic prices are used in many scenarios, e.g., flight ticketing, hotel room booking and ride-on-demand (RoD) service such as Uber and DiDi, and while they are beneficial for service providers, practitioners or users, they lead to the concern of privacy leakage – the possibility of learning user information from dynamic prices. In this paper, we aim to study this possibility and choose trip purpose mining in RoD service as an attack example, based on real-world large datasets. We discuss the criteria of choosing datasets – ubiquitous, collective and easily accessible – from the perspective of an attacker, and extract features describing trip information, spatio-temporal and dynamic prices context. The trip purpose mining problem is then solved as a multi-class classification problem and multiple binary-class problems. In the multi-class problem, we verify that dynamic prices information results in a 17.1% improvement in classification accuracy; in the binary-class problems, we quantify feature contributions and explain the different extents of privacy leakage in identifying different trip purposes. Our hope is that the study not only serves as a case study demonstrating the privacy leakage problem in RoD service, but also sheds light on such privacy problem in other services using dynamic prices and triggers more research efforts.
In this competitive world, companies should sustain good relationships with their consumers. CRM (customer relationship management) program can improve the company’s customer satisfaction; to satisfy customer need different processes and technique are established to make the CRM more effective. This research is proposed to determine the relationship between customer loyalty and retention. Also, this research examines the impact of Customer Relationship Management (CRM) on Customer Satisfaction. The target population of this study is customers of the tourism industry in India ( n = 300). Then, regression analysis is carried out in order to discover the link between the variables. This study result shows that service quality and employee behavior of customer need and satisfaction with the effect of different significant of positive relation of both the variables. To make the customer satisfied and to retain their company the CRM should be strong and reliable with the consumers. CRM plays a vital role in increasing market share, high productivity, improving in-depth customer knowledge, and customer satisfaction to increase consumer loyalty to the company to have a clear view of who is their customer, what are the need of their customer and how can satisfy their needs and wants their customers.
This research was conducted to analyze more deeply the influence of customer value and brand awareness on customer retention with customer satisfaction as a mediating variable. The survey data used in this research is based on the results of a questionnaire distributed online using a Google form consisting of 18 questions and filled in by 291 respondents. The data was then processed using AMOS version 23. The results of this research prove that customer value and brand awareness have a positive and significant effect on customer retention with customer satisfaction as a mediating variable. It is hoped that the results of this research will bring positive benefits to various parties, namely for business owners and the world of fast commerce as well as for science in theory development. This research has sample and time limitations. So it can be a suggestion for further research to conduct research with a larger sample and at a different time. So it is recommended for future researchers to dig deeper into the scope of quick commerce, research over a wider area and use different research methods.
This research paper investigates the impact of surge pricing, a dynamic pricing strategy that adjusts prices based on real-time demand and supply, on customers' perception of price fairness. We aim to provide insights for both academic and managerial audiences. Our study focuses on how businesses using surge pricing can minimize negative effects on customer behavior by properly communicating price changes. We conducted two experiments to examine customers' fairness perception of surge pricing policies. Our findings revealed that customers generally perceive surge pricing as less fair. However, we also discovered that aligning the amount of information shared with the price increase can effectively improve these fairness perceptions. Our research contributes to the literature on price communication by exploring factors that influence consumers' understanding and acceptance of price changes. Additionally, our findings offer practical guidance for businesses on how to communicate pricing information in a way that customers perceive as fair, ultimately benefiting both companies and their customers. ARTICLE HISTORY
In a world with enormous opportunities and challenges from the technology revolution and the lingering COVID-19 pandemic, customer retention is more important than ever for retailers. While marketing and advertising are limited in the tough time, retail operations become the salvage and dominance with the increasing sales recovered in 2021 thanks to food and essential business.
Currently, many researchers and reporters demonstrate that shopping behaviour has changed from offline to online and a combination of online and offline for the consumption of food and essential goods due to the ease of access to the Internet and the ownership of mobile devices, which has stimulated them to shop in modern retail channels more than ever. However, in recent years, minimal attention has been paid to the effects of store operations on changes in shopping
behaviour in retail. In particular, the contribution of store operations to customer benefits and customer retention is often less known by shoppers and is hardly measured accurately and adequately by management. Furthermore, the psychological effect on customer retention in supermarkets does not seem to be thoroughly discussed in existing studies.
Therefore, this thesis seeks to fill the gaps between academic knowledge and business practices in retail. With the foundation of commitment-trust theory, the thesis aims to develop and validate the operational model to increase customer retention in supermarkets by investigating the direct and indirect effects through perceived benefits of store’s Operational factors (classified into Merchandise- related and Service-related factors) under moderating role of psychological ownership. This study is conducted in Vietnam, an emerging country in the APAC, as empirical evidence.
For research achievement, qualitative research is conducted through in-depth interviews with 32 supermarket managers to obtain expert advice. Furthermore, a quantitative study is conducted through 493 questionnaire surveys to observe shoppers’ habits, behaviour, attitudes, beliefs, prejudices, preferences, motivations, and opinions of shoppers for store’s Operational factors, perceived customer benefit and customer retention in supermarkets. Partial Least Squares Structural Equation Modelling is associated with examining the cause-effect relationships among the factors through the relevant indicators.
The study findings offer an operational view of how store’s Operational factors
significantly contribute to customer retention. Simultaneously, it demonstrates how Perceived benefit mediates the relationships between the Operational factors and Customer retention and how Psychological ownership moderates the effect of Perceived benefits on Customer retention in supermarkets. Practically, research findings can be a reliable reference for researchers and professionals in the retail industry to forecast Customer retention based on store operations improvement and customers’ Psychological ownership.
Customer retention is vital for businesses with much research literature now available and in most cases, is regarded as an indicator of acquisition performance, but factors influencing it have rarely been studied in the serial acquirer context. Customer experience has drawn a great deal of attention from scholars and business practitioners in the past few decades. Successfully designing and providing customers with an optimal experience has become a central priority for marketing theory and practice. Customer experience plays a key role for firms in creating a sustainable competitive advantage and building good customer relationships The objective of this research is to determine the factors associated with customer retention. I presented a literature study using systematic literature review of relevant publications and as a result of this process, 19 articles are included and then examined the bibliographical references to check the validity of the inquiry and to avoid any potential omissions. I identify several variables that affect by customer retention.
This study examines the optimal pricing and pricing policy selection for a business-to-consumer (B2C) car-sharing platform during peak and off-peak hours, where two pricing policies are evaluated, that is, fixed pricing policy and dynamic pricing policy. First, we construct the B2C car-sharing market demand function and the sharing platform’s profit maximization model under each pricing policy, and obtain optimal outcomes by solving the model, including service price, market demand, platform’s profit, consumer surplus, and social welfare. Then, through analysis, we reveal the effects of the pricing policy selection on the optimal outcomes. The results show that compared with the fixed pricing policy, implementing a dynamic pricing policy can increase the sharing platform’s profit, but decrease the consumer surplus and social welfare. Additionally, implementing a dynamic pricing policy can also increase the demand during off-peak hours and decrease the demand during peak hours.
The sharing economy platforms facilitate collaboration across geographical boundaries and promote service innovation by reshaping traditional business networks. This study takes a Social Capital Theory perspective on how Social Capital (SC) is created on professional sharing economy platforms, with particular attention to the creative services industry. Our in-depth qualitative investigation draws on 35 interviews with freelance designers and platform clients based in 17 different countries. The study demonstrates that SC created outside sharing economy platforms is not readily transferred to these platforms, which represents a major difference from the dynamics of SC in more traditional settings. Furthermore, SC transfer between platforms is difficult. Building platform-specific SC ‘from scratch’ requires a significant effort and is highly dependent on reputation systems, in the form of ratings and reviews. We argue that the platforms’ reputation systems force members to become ‘slaves’ to ensuring their star ratings and reviews are as good as possible. In addition, we explore how platform members learn to build SC on the platforms beyond ratings and reviews. Overall, the study contributes to academic discussions on opportunities and challenges for service innovation within the sharing economy and introduces the application of Social Capital Theory to the context of sharing economy platforms.
The restaurant industry has yet to fully embrace revenue management (RM) in the form of peak-load pricing. Restaurateurs fear customers’ reactions to price increases could negatively impact their satisfaction and return intentions. In this study an experimental design was used to examine if the explanation provided to customers of a hypothetical restaurant that implemented peak-load menu pricing during periods of high (peak) demand would predict customers’ reactions. Reactions assessed included respondents’ suspicion of the restaurant, perceptions of pricing fairness and price-value, satisfaction, and return intentions. Additionally, the moderating effects of customers’ familiarity with RM and the direct effects of decisional control and income were assessed. Data from 409 respondents showed that higher suspicion was negatively associated with perceptions of pricing fairness and price-value, satisfaction, and return intentions during peak-demand periods (weekends). These lower return intentions, however, were also found for off-peak demand periods (weekdays) when no price increase had been implemented. The results suggest that suspicion, once activated, can lead to customer loss during both peak and off-peak demand periods, and that restaurant operators wanting to use peak-load pricing must carefully consider various factors in its implementation.
Purpose
This research explores causal combinations (personal traits, external factors and self-fulfillment) that could provide holistic views leading to sustainable start-ups via data collected from Taiwanese entrepreneurs.
Design/methodology/approach
The authors employ five-point Likert scale measurements in the questionnaires and fuzzy-set/Qualitative Comparative Analysis (fsQCA) for the investigation.
Findings
The study finds four types of sustainable entrepreneurs. Conservative resilient entrepreneurs have an absence of both openness and neuroticism. Conservative achieving entrepreneurs have an absence of openness and the presence of conscientiousness. Conservative-hired entrepreneurs have an absence of both openness and unemployment. Lastly, conservative opportunistic entrepreneurs exhibit an absence of openness and the presence of business opportunity.
Originality/value
The results add to the authors’ knowledge and understanding of the entrepreneurship literature and also offer implications for people who are interested in entrepreneurship as well as to policymakers wanting to promote new start-ups.
This research analyzes and forecasts the causal combinations of innovation for economic growth, utilizing yearly data from Organization for Economic Co-operation and Development (OECD) countries. Employing the method of fuzzy sets/Qualitative Comparative Analysis (fsQCA), the two causal combinations from the estimation are 1) Institute, Human Capital and Research, Infrastructure, and Market Sophistication as well as 2) Human Capital and Research, Infrastructure, Market Sophistication, and Business Sophistication. This study proposes a time series method to forecast fsQCA results that offer performances demonstrating strong predictive validities.
Retensi pelanggan penting untuk dianalisis agar perusahaan mampu menentukan berbagai strategi dalam mempertahankan pelanggan. Selain itu, retensi pelanggan merupakan satu tahap di atas loyalitas pelanggan sehingga perusahaan perlu untuk selalu mengetahuinya karena bermanfaat dalam pengelolaan pelanggan. Penlitian ini bertujuan untuk menganalisis pengaruh responsivitas dan biaya beralih terhadap retensi pelanggan. Sebanyak tujuh puluh responden yang dipilih pada penelitian ini yaitu mahasiswa pascasarjana (program master) untuk jurusan Manajemen Universitas Pendidikan Indonesia (UPI) yang menggunakan kartu seluler SIMPATI pada telepon genggam mereka. Sampel bertujuan merupakan teknik pengambilan sampel penelitian ini. Metode analisis pada penelitian ini menggunakan metode analisis regresi linier berganda dengan bantuan alat SPSS. Hasil penelitian menunjukkan bahwa secara simultan variabel responsivitas dan biaya beralih memiliki pengaruh terhadap variabel retensi pelanggan. Secara parsial, variabel responsivitas memiliki pengaruh terhadap variabel retensi pelanggan, sementara tidak untuk variabel biaya beralih. Nilai koefisien determinasi sebesar 0,146 yang berarti retensi pelanggan pada penelitian ini dijelaskan hanya sebesar 14,6% oleh responsivitas dan biaya beralih. Beberapa rekomendasi dinyatakan dalam artikel ini untuk kesempurnaan penelitian selanjutnya.
The following is a proposal for ride-hailing transport service, Grab. The proposal is done to assist them with the problems they face every now and then. Grabs’ Facebook page reveals myriad complaints about its services. Many app designers and even users have been facing several issues regarding their grab app. Since a lot of people rely on grab as their main transportation to go to places it is important for Grab to consider the criticism to improve their service. The main objectives definitely would be managing a good relationship with existing customers with a focus on creating loyalty towards their business. There are several solutions and recommendations that are included in this proposal to encourage Grab for their service enhancement.
The dimensions of transport development are closely linked with the socio-economic profile and technological level of a city. The entire trafficscape of the city of Kolkata evolved as the efficiency of the mass transport services declined, disposable income of the majority increased. There was gradual privatisation with increase in the share of para-transit modes. As the literate, technologically conversant urban population wanted a smarter alternative to regular taxis and auto rickshaws the app-based cab aggregator services brought in the silent revolution in the transport communication system. The main objectives of the paper are to bring out the essence of changing scenario, to access qualitatively and quantitatively that how far analysis of big data and reliance on technology through ICT and IoT has been able to meet the gap between expected and actual service delivery of the said para-transit mode through SWOT analysis, regression analysis and perception studies involving primary and secondary database and to have an idea about the future trajectory of this emerging app cab market. The study found that though majority of the commuters were satisfied with availability, reliability, cost effectiveness, safety, cashless option, driver behaviour, comfort and absence of bargaining there were issues regarding transparency and surge pricing. The drivers too were content with their improved earnings but were unhappy with the long hours and were apprehensive with regular incentive cuts. So, the situation is volatile with promising future if the companies manage to balance between the virtual capabilities and actual reality. Keywords: Para-transit, App cab aggregators, Technology, Big data, ICT, IoT
The online sharing economy can multiply the effects of its traditional counterparts. This study intends to explore consumer behavior for the sharing economy in the hotel industry. To that end, this study explores the relationships between variables for online and offline hotels to identify the differences in both relationships. In addition, this study compares the results from two research methods: structural equation modeling (SEM) and qualitative analysis with structural associations. The survey examines both Airbnb (online hotels) and conventional hotels. From SEM analyses for Airbnb and conventional hotels, all the variables have significant positive impacts on satisfaction, which then has a significant positive impact on repurchase intention. This study also discusses the differences in the coefficients for both targets. Qualitative analysis with structural associations supports different relationships and one unique relationship with structural associations for Airbnb.
On-demand service platforms (e.g., Uber, Lyft) match consumers with independent workers nearby at short notice. To manage fluctuating supply and demand conditions across different market locations (zones), on-demand platforms share market forecasts with workers, to inform them where they should be available, and use surge pricing, wherein the price in a particular zone is temporarily raised above the regular price. We analyze the strategic role of surge pricing and forecast communication in an on-demand marketplace, explicitly accounting for how they influence workers to move between zones. We show that, contrary to conventional wisdom, surge pricing can be useful even in zones where supply exceeds demand. Specifically, because of the strategic interaction amongst workers in their decisions to move between zones, simply informing workers about where they are needed is not sufficient to ensure that enough workers move to these zones. Interestingly, surge pricing in a zone with excess supply can induce a better distribution of workers by lowering workers' revenue potential of serving that zone, thereby inducing workers to move to zones needing more workers. Even though such surge pricing reduces platform profit in the zone where it is used, it can increase total platform profit across zones and be more profitable than offering workers bonuses to move. Surge pricing in zones with excess supply may also be used to credibly inform workers about their need to move to adjacent zones, or to minimize the number of workers leaving a zone. Our analysis offers insights for effectively managing on-demand platforms relying on independent workers.
A small change in prices can have a significant impact on profits and it is therefore becoming crucial for firms to use innovative approaches to pricing. Smart pricing is a dynamic approach to pricing that requires that firms have accurate information about market demand and profit margins on each item sold. Smart prices take into account differences in the costs of serving different segments and also the different valuations of one’s product by different segments. Firms that use smart pricing will not use a fixed price but will adjust prices, even on a daily basis, as market conditions, consumer demand, and product valuations change. Smart pricing is becoming extremely crucial for firms that wish to survive in the age of the Internet and globalization. Today’s customers use the Internet not only to make price comparisons but also to determine the seller’s actual costs.
Individual-level price discrimination, while not a new idea, is more than a theoretical possibility in the Internet age. Economic theory argues that dynamic pricing (i.e., individual-level price discrimination) is inherently good for the profitability of the firm, because it allows the firm to capture a larger share of the consumer surplus, but anecdotal evidence from recent retail experiments with Internet-based dynamic pricing suggests that consumers react strongly against this practice. Using a two-dimensional conceptualization of trust, based on benevolence and competence trust, the current experiment examines how the experience of a dynamic pricing event and the direction of the pricing discrimination (i.e., whether one is offered the higher or the lower price) affects both the mean levels of trust and the weight given to the separate trust dimensions in the formation of overall trust. Because demand-based pricing, such as dynamic pricing, is generally considered unfair, it is expected that trust levels will be lower and that more weight will be given to benevolence trust. Results show that mean benevolence trust is significantly lower (which leads to a marginal decrease in overall trust) and the weight given to benevolence trust in the formation of overall trust substantially increases. The direction-of-price-discrimination effects are generally unsupported. © 2003 Wiley Periodicals, Inc.
The past decade has seen a virtual explosion of information about customers and their preferences. This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost. At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners. These two developments are narrowly intertwined. Pricing decisions have a direct effect on operations and visa versa. Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice. This article reviews a number of key linkages between pricing and operations. In particular, it highlights different drivers for dynamic pricing strategies. Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field.
Problem definition: This paper explores the impact of competition between platforms in the sharing economy. Examples include the cases of Uber and Lyft in the context of ride-sharing platforms. In particular, we consider competition between two platforms that offer a common service (e.g., rides) through a set of independent service providers (e.g., drivers) to a market of customers. Each platform sets a price that is charged to customers for obtaining the service provided by a driver. A portion of that price is paid to the driver who delivers the service. Both customers’ and drivers’ utilities are sensitive to the payment terms set by the platform and are also sensitive to congestion in the system (given by the relative number of customers and drivers in the market). We consider two possible settings. The first one, termed “single-homing,” assumes that drivers work through a single platform. In the second setting, termed “multihoming” (or “multiapping,” as it is known in practice), drivers deliver their service through both platforms. Academic/practical relevance: This is one of the first papers to study competition and multihoming in the presence of congestion effects typically observed in the sharing economy. We leverage the model to study some practical questions that have received significant press attention (and stirred some controversies) in the ride-sharing industry. The first involves the issue of surge pricing. The second involves the increasingly common practice of drivers choosing to operate on multiple platforms (multihoming). Methodology: We formulate our problem as a pricing game between two platforms and employ the concept of a Nash equilibrium to analyze equilibrium outcomes in various settings. Results: In both the single-homing and multihoming settings, we study the equilibrium prices that emerge from the competitive interaction between the platforms and explore the supply and demand outcomes that can arise at equilibrium. We build on these equilibrium results to study the impact of surge pricing in response to a surge in demand and to examine the incentives at play when drivers engage in multihoming. Managerial implications: We find that raising prices in response to a surge in demand makes drivers and customers better off than if platforms were constrained to charge the same prices that would arise under normal demand levels. We also compare drivers’ and customers’ performance when all drivers either single-home or multihome. We find that although individual drivers may have an incentive to multihome, all players are worse off when all drivers multihome. We conclude by proposing an incentive mechanism to discourage multihoming.
Although Uber and Lyft are known for their flexible “surge pricing,” they are surprisingly rigid in another way: each firm takes a constant percentage of passenger fare whether or not there is a surge. In this paper, I investigate the possible reasons for, and the impact of, this rigidity. I study a market in which a profit‐maximizing intermediary facilitates trade between buyers and sellers. The intermediary sets prices for buyers and sellers, and keeps the difference as her fee. Optimal prices increase when demand increases, that is, shifts right. If a demand increase is due to an increase in the number of ex ante symmetric buyers, then the intermediary's optimal percent fee decreases. If, instead, a demand increase is due to a reduction in the elasticity of demand, then the intermediary's optimal percent fee increases. In either case, if the intermediary keeps a constant percent fee regardless of shifts in demand, as is the case with Uber and Lyft, then surge pricing (i.e., the ratio of price during high demand to price during low demand) is amplified on one side of the market and diminished on the other side.
Using three identification strategies, this paper finds that supply-driven oil price increases lowered U.S. stock returns in many sectors before the shale oil revolution but not after. It also reports that oil prices are a priced factor in a multi-factor asset pricing model both before and after the shale revolution. While oil prices mattered in both periods, the beneficial effects of oil price increases on the U.S. stock market have risen and the harmful effects have fallen since U.S. oil production soared after 2010.
On-demand platforms (e.g., Uber, Lyft) often rely on independent workers, who are not directly under the platform's control, to be available at the "right" time and locations to serve consumers at short notice. To manage fluctuating demand across market locations (zones), on-demand platforms share market forecasts with workers to inform them where they should be available, and use surge pricing-wherein the price at a particular zone is temporarily raised above the regular price. We analyze these platform strategies in an on-demand marketplace where independent workers can move between adjacent zones, explicitly accounting for the strategic interaction in their moving decisions. We show that, contrary to conventional wisdom, surge pricing can be useful even in zones where supply exceeds demand. Specifically, because workers are strategic agents facing costs to move and competition from other workers who move, simply informing workers where they should be available may not ensure that enough workers move to that zone. Interestingly, more workers can be made to move from a zone with excess supply of workers by strategically using a surge price to throttle demand in that zone. Such strategic surge pricing can increase total platform profit across zones, and even be more profitable than offering workers bonuses to move. Surge pricing in a zone with excess supply can also be useful to credibly communicate the need for more workers to move. In other instances, such surge pricing may be useful to avoid too many workers from moving. Our analysis offers insights for effectively managing on-demand service with independent workers.
Fuzzy set qualitative comparative analysis (fsQCA) is a novel and powerful methodology used as an analytical technique and research approach in the social science field. This study aims to extend the application of fsQCA in investigating the structural associations of antecedents and the outcomes in a multi-layer problem. The research framework of ethnic themed restaurants suggested by Lu et al. (2015) and the new consistency by Huarng (2016) were adopted. With the same data set, the findings from the systems approach and fsQCA confirmed the three and four dimensions of brand equity, respectively, which provided explanations for complexity theory, while reinforced fsQCA's appropriateness. From the managerial perspective, the study unraveled the need for managers to implement proper strategies to achieve the objective of higher retention.
An on-demand service platform connects waiting-time-sensitive customers with independent service providers (agents). This paper examines how two defining features of an on-demand service platform—delay sensitivity and agent independence—impact the platform’s optimal per-service price and wage. Delay sensitivity reduces expected utility for customers and agents, which suggests that the platform should respond by decreasing the price (to encourage participation of customers) and increasing the wage (to encourage participation of agents). These intuitive price and wage prescriptions are valid in a benchmark setting without uncertainty in the customers’ valuation or the agents’ opportunity costs. However, uncertainty in either dimension can reverse the prescriptions: Delay sensitivity increases the optimal price when customer valuation uncertainty is moderate. Delay sensitivity decreases the optimal wage when agent opportunity cost uncertainty is high and expected opportunity cost is moderate. Under agent opportunity cost uncertainty, agent independence decreases the price. Under customer valuation uncertainty, agent independence increases the price if and only if valuation uncertainty is sufficiently high.
The online appendix is available at https://doi.org/10.1287/msom.2017.0678 .
Surge pricing is commonly used in on-demand ridesourcing platforms to dynamically balance demand and supply, although it is controversial and has long stimulated debate regarding its pros and cons. In practice, there is usually a reasonable or legitimate range of prices. However, such a constrained surge-pricing strategy may fail to balance demand and supply in certain cases—e.g., even adopting the highest allowed price cannot reduce peak-period demand to a level at which the market clears without some form of non- price rationing. To address this limitation, we propose a novel reward scheme integrated with surge pricing: Passengers pay an additional amount to a reward account on top of the regular surge price during peak hours, then use the balance in their reward account to subsidize trips during off-peak hours. We propose models to describe the number of travel requests and the number of active drivers on the platform, and characterize the market equilibrium under several assumptions. We compare scenarios with and without the reward scheme from three perspectives: passenger utility, driver income, and platform revenue and profit. We find that in some situations, all three stakeholders—i.e., passengers, drivers, and the platform—will be better off under the reward scheme integrated with surge pricing.
We investigated the impact of customers’ image congruity and their satisfaction on customer retention at luxury restaurants. We examined the conspicuousness of product consumption as the moderator in the relationship of image congruity and customer satisfaction. Our assessment of the measurement model revealed acceptable levels of reliability and construct validity. Our findings from the structural model assessment indicated that both image congruity and customer satisfaction exerted an influence on customer retention that was sufficiently significant to explain the total variance in retention. In addition, results showed that customer satisfaction was prominent in determining retention, acting as a significant mediator. Conspicuousness of product consumption was a significant moderator of the relationship between image congruity and customer satisfaction. Overall, our findings offer researchers and practitioners in the luxury restaurant industry valuable information regarding customer retention. © 2018 Scientific Journal Publishers Limited. All rights reserved.
Previous studies have investigated drivers of customer retention in the mobile telecommunications industry worldwide. These studies call on scholars pay to attention to these factors in the scholarly marketing literature, since customer retention is the basic tenet of relationship marketing. Drawing on relationship marketing theory, this study analyzes the direct and indirect relationships amongst trust, commitment, and conflict handling on customer retention. A cross-sectional survey using a structured questionnaire was employed to gather data from customers of mobile telecommunication operators. The findings revealed that only conflict handling had a direct significant effect on customer retention. Also, trust and conflict handling had a direct and significant effect on customer satisfaction. However, trust and conflict handling were seen to have an indirect significant effect on customer retention via customer satisfaction. The study recommends that managers should effectively resolve customer complaints as well as build their trustworthiness in order to satisfy and retain their customers.
Much remains unknown about the clothing co-consumption practices of mothers and their teenage daughters, especially from a cross-cultural perspective. This study uses social comparison theory to examine how mothers engage in clothing co-consumption practices with their adolescent daughters and the effects on their likelihood of changing brands, stores, or styles. It includes 732 French and Japanese mothers who have adolescent daughters between the ages of 15 and 18. years. The structural equation modeling and qualitative analysis with structural associations reveal that Japanese mothers with high self-esteem enter into strong social comparisons, which lead to co-consumption practices (common shopping, joint purchases, clothing exchanges), whereas regardless of their levels of self-esteem, French mothers engage in social comparison processes that lead them to change their clothing styles, brands, and stores.
This study proposes equilibrium models under different behavioral assumptions of labor supply in a ride-sourcing market and then investigates the performance of surge pricing. A time-expanded network is first proposed to delineate possible work schedules of drivers. Based on the proposed network, we provide formulations and algorithms for both neoclassical and income-targeting hypotheses to characterize the labor supply of ride-sourcing drivers, i.e., their choices of work hours. We then investigate the impact of surge pricing using a bi-level programming framework, with the lower-level problem capturing the equilibrium work hour choices while the upper-level one representing revenue-maximizing surge pricing. Compared to static pricing, the platform and drivers are found to generally enjoy higher revenue while customers may be made worse off during highly surged periods. Lastly, a simple regulation scheme to reduce market power is discussed.
Uber, the ride-sharing company launched in 2010, has grown at an exponential rate. Using both survey and administrative data, the authors provide the first comprehensive analysis of the labor market for Uber’s driver-partners. Drivers appear to be attracted to the Uber platform largely because of the flexibility it offers, the level of compensation, and the fact that earnings per hour do not vary much based on the number of hours worked. Uber’s driver-partners are more similar in terms of their age and education to the general workforce than to taxi drivers and chauffeurs. Most of Uber’s driver-partners had full- or part-time employment before joining Uber, and many continue in those positions after starting to drive with the Uber platform, which makes the flexibility to set their own hours especially valuable. Drivers often cite the desire to smooth fluctuations in their income as one of their reasons for partnering with Uber.
Ride-hailing applications (apps) like Uber and Lyft introduced a matching technology and market design that recent research has found is more efficient than traditional taxi systems [2]. However, unlike traditional street-hailing taxi systems, they are prone to a failure mode first anticipated by [1]. In this paper we model and empirically establish the existence of these dynamics. We then show how surge pricing and, to a lesser extent, other market design interventions can prevent this problem from crippling a ride-hailing market.
An over-burdened dispatch system results in available idle drivers being too thinly spread throughout a city, forcing matches between drivers and passengers that are far away from each other. Cars are thus sent on a wild goose chase (WGC) to pick up distant customers, wasting drivers' time and reducing earnings. This effectively removes cars from the road both directly (as the cars are busy making pick-ups) and indirectly (as cars exit in the face of reduced earnings), exacerbating the problem. This harmful feedback cycle results in a dramatic fall in welfare, hurting both drivers and passengers. A ride-hailing market that falls into WGCs frequently might therefore perform worse than traditional street-hailing taxi systems, so it is essential to understand WGCs in order to design markets in a way that avoids WGCs and exploits the potential welfare gains from the new technology.
[1] dismissed WGCs as Pareto-dominated equilibria and thus just a theoretical curiosity. However, we show that when prices are too low relative to demand all equilibria of the market are WGCs when using a first-dispatch protocol, in which an idle driver is immediately dispatched every time a rider requests a trip (as many ride-hailing services have committed to).
This suggests two ways in which pricing can avoid WGCs. First, one might set a single high price all the time, sufficiently high to avoid WGCs even at peak-demand periods. Of course this design has the drawback that prices will be unnecessarily high, and thus demand inefficiently suppressed, at times of low demand. A more elaborate mechanism is to use dynamic ``surge pricing'' that responds to market conditions. Such a system was introduced by Uber early in its development. Prices are set high during peak-loads, but can fall when demand is more normal. Thus, against the common perception, surge pricing allows ride-hailing apps to reduce prices from the static baseline instead of increasing them.
Recent platforms, like Uber and Lyft, offer service to consumers via “self-scheduling” providers who decide for themselves how often to work. These platforms may charge consumers prices and pay providers wages that both adjust based on prevailing demand conditions. For example, Uber uses a “surge pricing” policy, which pays providers a fixed commission of its dynamic price. With a stylized model that yields analytical and numerical results, we study several pricing schemes that could be implemented on a service platform, including surge pricing. We find that the optimal contract substantially increases the platform’s profit relative to contracts that have a fixed price or fixed wage (or both), and although surge pricing is not optimal, it generally achieves nearly the optimal profit. Despite its merits for the platform, surge pricing has been criticized because of concerns for the welfare of providers and consumers. In our model, as labor becomes more expensive, providers and consumers are better off with surge pricing because providers are better utilized and consumers benefit both from lower prices during normal demand and expanded access to service during peak demand. We conclude, in contrast to popular criticism, that all stakeholders can benefit from the use of surge pricing on a platform with self-scheduling capacity.
The e-companion is available at https://doi.org/10.1287/msom.2017.0618.
The purpose of this paper is to explore the relationships among customer satisfaction of the 7Ps marketing mix, loyalty, customer retention, and market competitive status. This paper applies structural equation modelling to measure the satisfaction level of service quality by analysing the 7Ps service marketing mix to include the variables of product, pricing, place, promotion, physical evidence, process, and people in the Taiwan mobile market. The data are assessed and analysed based on 620 valid questionnaires via face-to-face interviews with subscribers of five operators. The results indicate that customer loyalty mediates the relationship between customer satisfaction and retention. The competitive status of market first-movers or followers moderates the relationships among customer satisfaction, loyalty, and retention. A firm’s competitive status moderates the direct effect of customer satisfaction on retention, and the first-mover group is superior to the follower group for this effect. A firm’s competitive status moderates the indirect effect between customer satisfaction and retention through loyalty, and the follower group is superior to the first-mover group for this effect. The findings provide management insights about the effects of satisfaction on retention and the effects of a customer’s cognitive framework on the firm’s competitive strategies.
We investigate Big 4 pricing over the period of 2000 to 2010. We classify the data into five periods: 2000-2001 as the pre-Sarbanes–Oxley Act (SOX) period, 2002-2003 as the SOX period, 2004-2006 as the Auditing Standard 2 (AS2) period, 2007 as the AS5 period, and 2008-2010 as the Great Recession period. The shocks to the audit market associated with these changes in auditing regulations and the economic environment have differential impacts on large clients and small clients. The percentage of small clients using Big 4 auditors dropped significantly over these shocks, whereas the percentage of large clients using Big 4 auditors experienced a large drop only from the SOX period to the AS2 period. We find that Big 4 pricing increased significantly from the pre-SOX period to the SOX period and continued to increase significantly in the AS2 period. Big 4 pricing experienced a significant decline in the AS5 period and declined insignificantly in the Great Recession period. Big 4 small firm pricing decreased significantly in the AS2 period compared with the SOX period and in the Great Recession period compared with the AS5 period. We find that the Big 4 pricing for small clients is contingent on the nature of competition. The Big 4 charged small firms higher prices in the SOX period, AS5 period, and Great Recession period when competition was lower. Our paper provides a unique contribution as a comprehensive analysis of Big 4 pricing and Big 4 small firm pricing.
For most products, price is the marketing variable customers react to more than any other. While this may be less so for luxury products, marketers of luxury brands still have to set a price. Most managers emphasize costs and competition when setting price. However, the third component of price, customer value or what a customer is willing to pay, is considered less often and is, in fact, much more important than costs and competition for luxury goods. Today, in this era of digital marketing, marketers have a greater ability to understand customer value and set a price accordingly. In this paper, new approaches to digital pricing that incorporate customer value are described and shown how they impact luxury good pricing.
One of the major differences between markets that follow a “sharing economy” paradigm and traditional two-sided markets is that the supply side in the sharing economy often includes individual nonprofessional decision makers, in addition to firms and professional agents. Using a data set of prices and availability of listings on Airbnb, we find that there exist substantial differences in the operational and financial performance of professional and nonprofessional hosts. In particular, properties managed by professional hosts earn 16.9% more in daily revenue, have 15.5% higher occupancy rates, and are 13.6% less likely to exit the market compared with properties owned by nonprofessional hosts, while controlling for property and market characteristics. We demonstrate that these performance differences between professionals and nonprofessionals can be partly explained by pricing inefficiencies. Specifically, we provide empirical evidence that nonprofessional hosts are less likely to offer different rates across stay dates based on the underlying demand patterns, such as those created by major holidays and conventions. We develop a parsimonious model to analyze the implications of having two such different host groups for a profit-maximizing platform operator and for a social planner. While a profit-maximizing platform operator should charge lower prices to nonprofessional hosts, a social planner would charge the same prices to professionals and nonprofessionals.
This study examines the determinants of customer satisfaction and customer loyalty in the Peruvian mobile phone market. Based in a survey to 1259 customers, Multinomial Logit and GSEM estimations show how determinants of customer satisfaction can be assessed when satisfaction is measured through ordered categorical data. The results confirm that in mobile phone market Customer Satisfaction influences strongly on Customer Loyalty, and in turn Loyalty is an important determinant of Customer Retention. In contrast with previous literature, this study identified the differentiated influence of diverse factors on positive and negative customer satisfaction categories. Indeed while results show that quality of service assessments made by customers had a significant impact on both negative and positive customer satisfaction categories; assessments of other service attributes like customer care, information on tariffs and plans and billing clarity, only showed a significant statistical influence on positive categories of customer satisfaction. Similar asymmetrical results were found with regard to other economic, socioeconomic and geographical determinants of customer decisions. As well, an analog effect is also observed in the relationship between customer satisfaction and loyalty, where only positive satisfaction assessments helps to explain the loyalty of users. Finally, results show that while satisfaction can be identified as a powerful cause of CR, switching barriers did not deter more demanding customers to switch to alternative carriers, suggesting that recent pro-competition regulatory reforms implemented in Peru contributed to reduce these barriers to competition in mobile markets.
This study proposes an approach to analyze the structural associations in multi-layer problems using the new consistency. Research methods are important in identifying correct associations between antecedents and outcomes. Studies suggest using fuzzy set Qualitative Comparative Analysis (fsQCA) to explore the associations. However, fsQCA presents two problems: the definition of consistency function and the propagation of consistency values in multi-layer problems. To facilitate the explanation, this study uses the proposed approach to analyze the structural research framework and data by Lin et al. (2009) to demonstrate the process of how to obtain the structural association of a multi-layer problem.
This study intends to explore the associations between the energy consumption relevant antecedents and economic development by using fuzzy set/Qualitative Comparative Analysis (fsQCA). FsQCA yields the causal recipes (causal combinations) for the outcome, GDP. The energy relevant data are from the U.S. Energy Information Administration and economic relevant data are from the International Monetary Fund. The analysis results provide two groups of causal recipes: One group explains the conditions for knowledge-intensive industrialized economies and the other explains those conditions for traditional industrialized economies. Both groups lead to high GDP. The results illustrate that only one equation may be insufficient to describe the associations between the energy consumption relevant antecedents and the economic development. This study also applies multivariate regression analysis (MRA) for similar analysis. The results report that not every variable of each individual year is significant, thus reflecting the problem of MRA.
Customer relationship management (CRM) is perceived to be failing, and there is an urgent need for some practical ways to address this issue. The research presented in this article demonstrates that the implementation of CRM activities delivers greater profits. Using calculations of the lifetime value of customers in two longitudinal case studies, the research finds that customer management strategies change as more is discovered about the value of the customer. These changes lead to better firm performance. The contribution of this article is to show that CRM works and that a relatively straightforward analysis of the value of the customer can make a real difference.
Healthcare is turning a big business. A better understanding of the factors affecting healthcare expenditure (HCE) can assist expenditure control. This study uses fuzzy set/Qualitative Comparative Analysis (fsQCA) to explore the sufficient conditions for the outcome, HCE. FsQCA provides causal recipes for each year to show the causal complexities leading to the outcome of that year with high consistencies. The three most recurrent causal recipes are: (1) longevity countries with many doctors and aging population; (2) longevity and rich countries with many doctors; and (3) longevity and rich countries with aging population. The analysis also shows strong predictive validities. The causal recipes of the first few years can successfully forecast the causal recipe(s) of following years.
This study intends to establish configural theory for ICT development by using fuzzy set/Qualitative Comparative Analysis (fsQCA) and to contrast the results with those from multivariate regression analysis (MRA). The fsQCA results support three propositions: the highly-developed countries, the highly-developed countries with low population density and the highly-developed countries with low corruption are the sufficient conditions for high ICT development. In addition, the improvement toward developed countries and increases in both population density and corruption are a sufficient condition for the improvement in ICT development. However, fsQCA finds a contrary case: the improvement toward developed countries and decreases in both population density and corruption are also a sufficient condition for the improvement in ICT development. MRA is good at model fitting. FsQCA is good at showing the causal complexities to explain the outcome and successfully predicts the withheld data sets.
Most previous research on consumers' switching intention has focused on individual variables that have immediate effects on consumers' intentions or behaviors, rather than analyzing it as a complex phenomenon. This article provides evidence that some service provider behaviors precipitate relationship dissolution, whereas other behaviors create a predisposition to switch. This different effect is observed through the mediating effect of customer satisfaction. While poor service quality and low firm commitment undermine consumer satisfaction and have only an indirect effect on switching intentions, price unfairness and anger incidents have a strong effect on switching, both directly and indirectly through satisfaction. Implications are discussed for customer relationship management. © 2007 Wiley Periodicals, Inc.
The practice of offering discounts to prospective customers represents a rudimentary form of using transaction history measures to customize the marketing mix. Furthermore, the proliferation of powerful customer relationship management (CRM) systems is providing the data and the communications channels necessary to extend this type of pricing strategy into true dynamic marketing policies that adjust pricing as customer relationships evolve. In this paper, we describe a dynamic programming–based approach to creating optimal relationship pricing policies. The methodology has two main components. The first component is a latent class logit model that is used to model customer buying behavior. The second component is a dynamic optimization procedure that computes profit-maximizing price paths. The methodology is illustrated using subscriber data provided by a large metropolitan newspaper.
The empirical results provide support for the common managerial practice of offering discounts to new customers. However, in contrast to current practice, the results suggest the use of a series of decreasing discounts based on the length of customer tenure rather than a single steep discount for first-time purchasers. The dynamic programming (DP) methodology also represents an important approach to calculating customer value (CV). Specifically, the DP framework allows the calculation of CV to be an explicit function of marketing policies and customer status. As such, this method for calculating CV accounts for the value of managerial flexibility and improves upon existing methods that do not model revenue and attrition rates as functions of marketing variables.
In certain purchase situations, such as when a new car is purchased and an old vehicle is traded in, individuals simultaneously play the role of buyers and sellers. It is interesting to observe that, when evaluating the purchase and selling prices of the new and old products respectively, such consumers often fail to behave rationally. For example, a discount on the price of the new commodity and an equivalent markup on the old product will be weighted differently. This empirical phenomenon can be analyzed with the aid of the prospect theory - an approach based on the descriptive decision theory. This theory facilitates the elaboration of decision-making rules for determining the optimum purchase or selling price from the supplier's point of view. An analytical causal study conveys an idea of the significance of this aspect of pricing policy for consumer satisfaction with the purchase act. Specifically, the study examines how the attractiveness of the offer impacts on and combines with satisfaction with deal, customer service, and condition of the vehicle to determine satisfaction with the vehicle purchase. (C) 2002 Wiley Periodicals, Inc.
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