Bike sharing and users’ subjective well-being: An empirical study in China

Ma, Liang; Xin, Zhang; Ding, Xiuzhen; Wang, Gaoshan

doi:10.1016/j.tra.2018.08.040

Cited by 64 publications

(64 citation statements)

References 58 publications

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“…An online survey was used to determine how a specific set of cognitive and emotional factors affected a person's decision to switch to a different product brand. For credibility and diversity, this study collected the questionnaire with the assistance of a leading Chinese internet research firm, Sojump.com, a platform that has been used in numerous previous studies [35,36]. The data was collected in August 2017, and all of the participants were required to have had an online shopping experience.…”

Section: Data Collectionmentioning

confidence: 99%

Identifying Factors Preventing Sustainable Brand Loyalty among Consumers: A Mixed Methods Approach

Zhang

Ding

et al. 2018

Sustainability

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Consumers' brand-switching behavior, or the non-sustainability of consumer loyalty to a brand, brings huge losses to affected companies. Thus, the investigation of factors behind consumers' brand-switching is very important. The study analyzes the mechanism and configuration of brand-switching intention in order to provide guidelines for increasing brand competitiveness. Using empirical analysis (SEM) and qualitative comparative analysis (fsQCA), this study elucidates the motives and mechanisms in operation when customers decide whether to stay with a particular brand or switch to an alternative. The data was collected in August 2017. The results of SEM showed that the attractiveness of an alternate brand had a negative influence on current brand image recognition and brand value recognition, which could produce negative emotions that then lead to a brand-switching intention. The fsQCA uncovered six combinations or configurations of variables that could lead to brand-switching. This study has both theoretical and practical outcomes for competitive branding.Sustainability 2018, 10, 4685 2 of 13 for brand conversion intentions; however, most research has directly addressed the factors influencing brand-switching [4][5][6] rather than systematically analyzing the internal influencing mechanism and effective formation path of brand conversion intentions. To fill these gaps, our study utilized cognition theory in order to explore the mechanisms and configurations of brand-switching intention. Alternative attractiveness, negative brand image recognition, negative brand value recognition, negative brand emotion and website anxiety were included in this study in order to determine their mutual effects on the decision to stay with a particular brand or to switch to a new one.This paper is organized into specific sections. Following the introduction in Section 1, the theoretical background is discussed and a literature review is presented in Section 2; the research model and hypotheses are also considered. In Section 3, the research methodology, including measurement and data collection, is described, and in Section 4 the data is analyzed. Section 5 includes discussion and interpretation of the results, and the conclusions are summarized, offering some theoretical and practical implications. Lastly, this study considers the limitations and raises the prospect of future studies in Section 6.

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Section: Data Collectionmentioning

confidence: 99%

Identifying Factors Preventing Sustainable Brand Loyalty among Consumers: A Mixed Methods Approach

Zhang

Ding

et al. 2018

Sustainability

Self Cite

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“…The questionnaire method was used to validate the conceptual model ( Table 1). All of the measured items were taken from other published studies: service quality was adapted from Oghuma, et al [43]; system quality was from Chen [44]; perceived usefulness and perceived ease of use were taken from Ma, et al [4]; habit was adapted from Xin, et al [2]; customer satisfaction was derived from Zhang, et al [45]; and, finally, the measures of continued usage intention were adapted from Bhattacherjee [20]. The questionnaires gauged responses on a 7-point Likert scale.…”

Section: Variables and Measuresmentioning

confidence: 99%

“…A review of the existing literature on bike sharing, showed that studies mainly focused on factors influencing the choice of bicycle [1,2]; shared bike use behavior [3]; shared bike users' subjective well-being [4]; the diffusion of public bike sharing systems [5]; the influence of bike sharing on other transportation modes such as car use [6]; the impact of weather conditions on bike use [7]; the effects of the built environment on bike sharing demand [8]; bike share rebalancing strategies, patterns, and purposes [9]; bike share safety [10]; bike share demand [11]; impact of pricing and transit disruptions on bike sharing [12]; optimization models for bike-sharing problems with transshipment [13]; bike share stations [14]; bike sharing travel patterns [15]; and, the shared bike users' recommendations [16]. However, few studies have examined what controls the shared bike users' intentions to continued or discontinued usage of shared bikes.…”

Section: Introductionmentioning

confidence: 99%

How to improve users’ intentions to continued usage of shared bicycles: A mixed method approach

2020

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Sharing the use of a bicycle in China has changed people's daily travel modes. Existing studies mainly explored the factors affecting individuals' initial intentions to start using a shared bicycle, but few looked at the likelihood that a user would continue using one. Based on a post-acceptance model of information system (IS) continuance, this investigation proposed a research model to investigate factors influencing riders' intentions to continued usage of shared bikes. Analysis involved structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) on data from 376 shared bicycle riders. The results from SEM showed that perceived usefulness, service quality, riders' habits, overall satisfaction and the nature of the weather were the most important factors positively influencing users' intentions to continue bike sharing. The results from fsQCA showed that six combinations of these variables were sufficient to explain continued usage. The conclusions of this study can be useful for operators to improve shared bicycle services.

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“…Scholars studied the social effects of shared bikes: the membership increase of shared bikes seemed to be slightly due to contagion from neighboring membership [29]. Social influence has a positive effect on users' trust attitude and hence subjective well-being [30]. According to a structural equation model (SEM) of intentions, the significance of factors is a sequence of subjective norms > attitude > perceived pleasure > effects of flexibility and convenience [31].…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing

Bian

Shu³

2020

Sustainability

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As a clean, sustainable transport tool, bicycles have significant advantages in short-distance travel. Despite many efforts assumed in Beijing to improve the cycling environment, the popularity of cycling remains relatively low. However, the advent of the free-floating bike-sharing (FFBS) system has engendered an unexpected cycling enthusiasm in Beijing. Therefore, it is of great importance to delve into why travelers prefer FFBS as a transportation form from a psychological perspective. In this paper, 352 valid questionnaires were collected from an online survey, and an extended theory of planned behavior (TPB) was adopted to examine the psychological determinants of intention and actual behavior to use FFBS. The results showed that men and car-owners prefer vehicles and show a lower willingness to use FFBS. In contrast, residents under the age of 60, residents with FFBS riding experience, and residents skilled in cycling are inclined to use FFBS; the economic convenience of FFBS is the most important attractant for FFBS, while bad weather is the biggest hindrance factor for residents to use FFBS; however, imperfection in infrastructure has no significant impact on reducing residents’ willingness to use FFBS. These results have important implications for planners to better understand the FFBS use behavior, and several suggestions are proposed to support the policymaking about FFBS.

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Bike sharing and users’ subjective well-being: An empirical study in China

Cited by 64 publications

References 58 publications

Identifying Factors Preventing Sustainable Brand Loyalty among Consumers: A Mixed Methods Approach

Identifying Factors Preventing Sustainable Brand Loyalty among Consumers: A Mixed Methods Approach

How to improve users’ intentions to continued usage of shared bicycles: A mixed method approach

Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing

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