当期荐读 2023年第3期 | 平台经济反垄断对社区团购用户不持续使用意愿的影响:基于感知价格和期望不一致的视角
图 | Internet
刘启华 彭思婕 许立扬 周婧怡
海南大学管理学院,海口,570228
摘要 / Abstract
平台经济反垄断政策影响下,社区团购平台不能再通过低价倾销或高额补贴等方式吸引用户。这会影响社区团购用户的持续使用行为吗?本文基于感知价格和期望不一致的视角,构建平台经济反垄断政策影响社区团购用户不持续使用意愿的研究模型,采用PLS-SEM对542份来自于社区团购用户的调查数据进行统计分析。
研究发现,在平台经济反垄断政策的影响下,社区团购用户感知价格上升引发产品质量不一致和服务质量不一致,进而感到不满意,导致出现不持续使用意愿。而且,对于价格敏感性高的用户,感知价格上升会导致更大的产品质量不一致,却不会导致更大的服务质量不一致。本文主要有三点理论贡献。第一,丰富了在线用户行为相关研究。在平台经济反垄断政策影响下,随着高额补贴等现象的消失,社区团购用户的感知价格可能会上升进而影响他们的使用行为,这是现有文献很少考虑到的。本文从感知价格视角分析平台经济反垄断政策对在线用户使用意愿的影响,对在线用户行为相关研究进行完善。第二,拓展了期望不一致理论。本文将用户的期望不一致细分为产品质量不一致和服务质量不一致,并考虑价格敏感性和时间意识在感知价格与产品质量不一致和服务质量不一致关系中的调节作用。第三,揭示平台经济反垄断政策通过影响在线用户使用行为实现平台治理的内在机理,对平台治理相关研究进行补充。研究发现,平台经济反垄断政策的实施使得在线用户对社区团购平台有更高的期望,倒逼平台提升产品和服务的质量,并通过优胜劣汰效应促进平台经济健康发展。
在研究方法上,本文在PLS-SEM的基础上,增加四种检验方法增强研究结果的客观性。第一,使用SPSS和AMOS对数据进行Harman单因素检验和变量标记法检验,排除共同方法偏差的影响。第二,使用SPSS进行无反应偏差测试,检验性别和年龄等在早期反应者和晚期反应者之间是否具有显著差异。第三,增加重要性能图分析(IPMA),将结构模型的总效果(重要性)与潜在变量得分(性能)的平均值进行比较,为管理建议的提出提供有力证据。第四,使用Stone-Geisser检验和blindfolding算法等非参数检验方法检验预测相关性。本文也为社区团购平台的管理者、商家和监管者等提出众多促进社区团购健康快速发展的对策。
关键词
平台经济反垄断 平台治理 期望不一致理论 不持续使用意愿 社区团购
Abstract
Against the backdrop of the anti-monopoly of platform economy, community group-buying platforms are no longer able to dump goods at low prices or provide high subsidies to attract users. Will online users continue to use community group-buying? From the perspective of perceived price and disconfirmation, this study constructs a theoretical model of users' community group-buying discontinuance intention influenced by the anti-monopoly of platform economy and uses PLS-SEM to analyze data from 542 valid users. It is found that, as a result of the anti-monopoly effect of platform economy, an increase in perceived price leads to product quality disconfirmation and service quality disconfirmation, thus increasing dissatisfaction, which positively affects discontinuance intention. In addition, for users with high price sensitivity, the increase in perceived price leads to greater product quality disconfirmation, but not to greater service quality disconfirmation. This study enriches and expands the research on online users' discontinuance intention, expectation-disconfirmation theory, and platform governance, which provides useful suggestions for platform merchants, managers, and regulators.
Keywords
Anti-monopoly of platform economy; Platform governance; Expectation-disconfirmation theory; Discontinuance intention; Community group-buying
向上滑动阅览
01
Introduction
Due to the COVID-19 pandemic, community group-buying has undergone explosive growth in China, with the market transaction scale reaching 18.68 billion yuan in 2021, a year-on-year increase of 60.4%, and the number of users reaching 646 million, up 37.44% year-on-year[1].
Along with the rapid development, the platform economy, including community group-buying platforms, has encountered novel development problems, which have attracted much attention of regulatory agencies in various countries. For example, low-price dumping phenomena such as “one-penny shopping” and “one-yuan shopping” have emerged. Accordingly, the Draft Anti-Monopoly Guidelines of Platform Economy was issued in 2021[2].
With the promulgation and implementation of anti-monopoly policies of platform economy, community group-buying has been forced to adjust the strategy of using low prices and high subsidies to attract users, which hindered retaining existing ones. Because of the significant loss of users, many community group-buying platforms, such as Tongcheng Shenghuo and Shixianghui, went out of business[3]. Therefore, how to retain existing users has become a key issue for community group-buying platforms and it is very important to understand the influence of the anti-monopoly of platform economy on the discontinuous use behavior of community group-buying platform users and take effective measures to retain existing users, which has rarely been discussed in previous literature.
In recent years, researchers in many fields, such as mobile social media[4,5], mobile shopping[6], mobile services[7,8], and mobile trading systems[9], have investigated mobile users’ discontinuance intentions. At present, many community group-buying platforms are facing the problem of user loss because of the anti-monopoly of platform economy, but previous literature has scarcely addressed this problem. The expectation-disconfirmation theory (EDT)[11] is widely used in the literature on discontinuance intention, which proves that disconfirmation is an important factor of discontinuance intention. However, users have various expectations of community group-buying, so it is necessary to subdivide disconfirmation, which cannot be explained by the current literature. Moreover, most of the literature focuses on product quality disconfirmation[10], while research on service quality disconfirmation remains insufficient. However, the logistics and distribution service requirements are high when community group-buying is used to purchase fresh vegetables and fruits.
The contributions of this study are summarized as follows. First, our study contributes to the existing literature on online users’ discontinuance intention. We consider the increase in perceived price caused by the anti-monopoly of platform economy and introduce it into the context of community group-buying to explore users’ discontinuance intention. Second, this paper extends the expectation-disconfirmation theory (EDT) by adding price sensitivity and time consciousness as moderators of the effects of perceived price on product quality disconfirmation and service quality disconfirmation. Third, this study has implications for research on platform governance. It reveals that the anti-monopoly of platform economy optimizes platform governance by influencing user behavior. We find that product quality disconfirmation and service quality disconfirmation predicted by perceived price affect users’ dissatisfaction and then lead to discontinuance intention.
02
Literature review
2.1 Research on mobile users’ discontinuous use
Discontinuance is not the opposite of continuance, nor does it necessarily represent the end of the life cycle of an information system[12]. Discontinuous use intention refers to users’ intention to alter their current levels of system use, including usage reduction, usage termination, temporary discontinuance, or replacement[13].
Given the swift evolution of the Internet and mobile terminals, various mobile applications have rapidly gained popularity, leading to fierce competition. Many scholars have recently studied mobile users’ discontinuous use intention to address the problem of user loss, as shown in Table 1. Their main theoretical frameworks include the stressor-strain-outcome (SSO) framework, the stimulus-organism-response (SOR) framework, EDT, the push-pull-mooring (PPM) framework, and others.
Table 1 Research on mobile users’ discontinuance intention in the past five years
(1)Research based on the stressor-strain-outcome framework: The SSO framework can effectively explain stress-related factors. Overload theory refine stressor factors while fatigue theory refine strain factors, revealing how stressor factors affect outcomes through strain factors. Stressor factors include not only social, information, and communication overload, but also social network exhaustion and the compulsive use. Strain factors include dissatisfaction, regret, and depression, which directly affect discontinuous use intention[14,29,30].
(2)Research based on the stimulus-organism-response framework: On social media, overuse refines stimulus factors, while users’ internal psychological states refine response factors. Stimulus factors include the overuse of social networking sites and social, information, and communication overload. Organism factors include feelings of guilt, fatigue, exhaustion, fear, and anxiety, which directly affect discontinuous use intention[4,13,15,22].
(3)Research based on EDT: Based on EDT, other models or variables are introduced in the research. For example, Wu et al.[7] adopt EDT and the functional theory of upward counterfactual thinking, which considers no-value perception the determinant of discontinuous intention. The moderation effect of price sensitivity has also been explored. Tang et al.[16] have developed and verified a scale of followers’ unfollowing motivations regarding brand fan pages (BFPs) by using the technology acceptance model and conducting a mixed-method study.
(4)Research based on push-pull-mooring framework: Based on systematic summaries of pushing factors, pulling factors, and mooring factors, users’ discontinuous and switching behavior have been discussed. Research results show that the push factors for users to stop using Facebook include Facebook fatigue and dissatisfaction and that the pull factors include alternative attractiveness. Mooring factors are personal norms and habits[5]. Other studies have discussed the switching behavior of users of mobile payment service platforms. The push factors include regret predicted by dissatisfaction, the pull factors include alternative attractiveness, perceived network size, and perceived complementarity, and the mooring factors include inertia[21].
(5)Research based on other frameworks: Luqman et al.[14] have employed self-determination theory and the theory of planned behavior, noting that user autonomous and controlled motivation have positive impacts on discontinuance intention. Chen et al.[6] used stress-coping theory to reveal that users are influenced by information overload and perceived intrusiveness, and decide whether to adopt disturbance handling or self-preservation strategies according to different rewards. Kim et al.[9] have reviewed postadoption studies and the limitations of mobile devices, finding that user attention is a key determinant that influences user discontinuance intention regarding mobile trading systems.
SSO, SOR, EDT, PPM, and other theoretical frameworks have been widely used in the research on mobile users’ discontinuous use behavior, revealing the impact mechanism of users’ discontinuance intention in the fields of mobile shopping, mobile SNS, and mobile service. However, little attention has been paid to the community group-buying. Influenced by the anti-monopoly of platform economy, users’ discontinuance intention is crucial to the survival of community group-buying.
2.2 Research on community group-buying users’ behavior
Group buying occurs when a group of consumers with the same needs gather to exercise strong bargaining power and purchase products or services at discounted prices[31]. Some studies have discussed the factors that influence online group buying users’ participation intention. For example, Klein and Sharma[32] have analyzed the collective impact of consumer decision-making styles and consumer involvement. Researchers have also considered the effect of group buying promotions and selling strategies. For example, Chou[33] suggests that countdowns expressed with a contracted scale are more effective than those expressed with an expanded scale.
Given the swift evolution of the mobile internet and social media, community group-buying has emerged and developed rapidly. Community group-buying refers to location-based group buying and community residents make group purchases (mainly of daily necessities) via mobile social media (such as WeChat in China) or other apps (such as Vanfruits in Canada). Previous research considered the characteristics of community group-buying and users’ motivations[34]. Literature also discussed the perspective of strategy[35]. However, this literature provides only a limited theoretically grounded understanding of what motivates users’ community group-buying discontinuance intentions. Therefore, it is necessary to supplement this literature by developing and empirically testing a research model of community group-buying users’ intentions to discontinue use.
2.3 Research on expectation-disconfirmation theory
EDT was first proposed by Oliver[11] to predict consumer satisfaction and purchase intention. According to EDT, disconfirmation occurs when a gap exists between consumers’ prepurchase expectations and postpurchase experiences. There are two types of disconfirmation: one is positive disconfirmation, which occurs when consumers’ postpurchase experiences are better than their prepurchase expectations; the other is negative disconfirmation, which occurs when consumers’ postpurchase experiences are worse than their prepurchase expectations[11,36]. When consumers’ expectations increase, negative disconfirmation is more likely to occur, because high expectations can easily be negated[37]. When negative disconfirmation is higher, dissatisfaction is greater, which leads to consumers’ discontinuous use intentions and behaviors[11].
The majority of relevant studies have proven that EDT can reliably predict consumers’ dissatisfaction and discontinuance intention. Thus, it has been widely used to evaluate consumers’ perception, dissatisfaction, and discontinuance intention. For example, in terms of consumers’ perception, Cai and Chi[38] discuss the influence of food pictures on consumers’ expectations and perceived performance amid different levels of disconfirmation. Abrate et al.[10] demonstrate that disconfirmation is stronger than the placebo effect in both value evaluation and quality evaluation. In terms of consumers’ dissatisfaction, Wu et al.[7] demonstrated that disconfirmation influences discontinuous use intention through perceived dissatisfaction. In terms of consumers’ discontinuance intention, previous studies have mainly applied EDT to evaluate this intention across services[7], social media[16],and communication technologies. However, the EDT literature has not yet proven the influence of disconfirmation on users’ discontinuance intention affected by the anti-monopoly of platform economy. Moreover, most studies have discussed the impact of expectation on the final evaluation of products or services, paying less attention to the process that leads to disconfirmation. Hence, in the context of anti-monopoly of platform economy, the influence of perceived price on disconfirmation remains elusive, and how different types of consumers reaction is still unclear.
03
Research model and hypotheses
3.1 Disconfirmation, dissatisfaction, and discontinuous use intention
Dissatisfaction reflects a negative attitude toward or a sense of valuelessness concerning products or services after purchase[7]. Discontinuance intention is thus defined as users’ intention to stop using a community group-buying platform, including usage reduction, usage termination, temporary discontinuance, or replacement[13]. Dissatisfaction directly affects consumers’ discontinuance use intention. When consumers experience dissatisfaction, they are likely to stop using the product or service in question[7]. Tang et al.[16] have found that dissatisfaction with quality information leads consumers to stop following brand fan pages. Wu et al.[7] also note that dissatisfaction plays a pivotal role in encouraging users to pay less attention to mobile instant messaging services.
Accordingly, when users are dissatisfied with a community group-buying platform, they fend to exhibit discontinuance use intention. The following hypothesis is therefore proposed:
H1: Users’ dissatisfaction positively affects their discontinuance use intention regarding community group-buying.
According to EDT, negative disconfirmation occurs when the performance of products or services fails to meet consumers’ expectations[39]. Bai et al.[40] have found that perceived food quality and perceived service quality play substantial mediating roles in the relationship between daily special offers and restaurant ratings. Moreover, for products such as fruits and vegetables, users expect prompt delivery to ensure the freshness and taste. Therefore, product and service quality evaluations account for the vast majority of judgments made by consumers concerning products on community group-buying platforms. For example, on Duoduo Maicai, most users have commented on the freshness, taste, weight of vegetables and fruits, logistics, and customer service levels provided. Therefore, in this paper, we divide disconfirmation into product quality and service quality disconfirmation. Product quality disconfirmation refers to situations in which the quality of the products sold on a community group-buying platform does not meet users’ expectations. Service quality disconfirmation refers to situations in which the quality of services provided by a community group-buying platform does not meet users’ expectations.
According to EDT, consumers’ dissatisfaction is positively affected by their expected disconfirmation. The degree of dissatisfaction depends on the degree of negative disconfirmation[11]. The following hypothesis is therefore proposed:
H2a: Product quality disconfirmation positively affects users’ dissatisfaction with community group-buying.
H2b: Service quality disconfirmation positively affects users’ dissatisfaction with community group-buying.
3.2 Perceived price and disconfirmation
Perceived price refers to a user’s subjective perception of price, that is, whether a product is expensive or inexpensive with respect to the user’s ability to pay[41]. Many catering companies have issued a substantial number of coupons to improve their competitive advantage, and these coupons affect consumers’ perceived price[42]. In addition, As a result of the anti-monopoly nature of the platform economy, operators are unable to sell below cost; Conseguently, red envelope subsidies, ultralow-priced products, and product discounts continue to decrease, resulting in an increase in users’ perceived price. This may lead to higher expectations regarding the product or service quality offered by a community group-buying platform[10]. However, two situations must be considered in this context. When postpurchase perceived performance exceeds prepurchase expectation, positive disconfirmation results. If not, then negative disconfirmation occurs. Nevertheless, high expectations can be easily negated[37], that is, the negative distance between perceived performance and expectations increases as expectations regarding products or services rise, thereby increasing the likelihood of negative disconfirmation.
Moreover, compared to offline vegetable markets and shopping malls, the fruits and vegetables sold via community group-buying platforms are less fresh. According to a report from a Chinese media consulting company, 19.8% of users believe that products bought via community group platforms are not sufficiently fresh[43]. In addition, due to the effects of COVID-19, many mobile users buy fruits and vegetables on community group-buying platforms during their home quarantine. As the pandemic is gradually brought under control, vegetable markets and offline shopping malls have resumed operations, providing mobile users with more buying options and diminishing the convenience advantage of community group-buying. Therefore, we assume that an increase in perceived price may cause a higher expectation for product quality and service quality, resulting in product and service quality disconfirmation. The following hypothesis is therefore proposed:
H3a: Perceived price positively affects product quality disconfirmation in community group-buying.
H3b: Perceived price positively affects service quality disconfirmation in community group-buying.
3.3 The moderating effect of price sensitivity
Price sensitivity refers to “individual users’ perception and reaction to the price or price change of products or services” and describes the degree to which people attach importance to prices[44]. Consumers with high price sensitivity care more about prices and respond more notably to price changes than those with low price sensitivity[45]. Price sensitivity is thus often a critical factor in consumption decisions and may even outweigh perceived value, regardless of whether it is positive or negative[7].
Price sensitivity is influenced by many factors, such as innovation[44], power distance[46], and gender identity. Generally, people who pursue high-quality products and services are less price sensitive than those who prefer inexpensive goods. However, consumers with high price sensitivity may exhibit higher product and service quality uncertainty than consumers with low price sensitivity. When their perceived price increases, users with high price sensitivity respond more intensely to this price change and are more inclined to evaluate it based on their experiences of value rather than affective components[45]. To maximize the benefits, such consumers have higher expectations regarding product and service quality, thus leading to an increase in their product and service quality disconfirmation. The following hypothesis is therefore proposed:
H4a: The impact of perceived price on product quality disconfirmation in community group-buying is strengthened by price sensitivity.
H4b: The impact of perceived price on service quality disconfirmation in community group-buying is strengthened by price sensitivity.
3.4 The moderating effect of time consciousness
Time consciousness refers to users’ awareness of time as a precious resource, which causes them to plan the use of their time carefully[47]. Consumers with stronger time consciousness excel at allocating time, use their time effectively, and seek time-saving shopping options based on their goal orientation[48]. Such consumers pursue fast and convenient electronic services and hope to obtain time-related benefits[49]. Thus, community group-buying users with strong time consciousness give more attention to service convenience and have higher expectations of service quality, resulting in their high degree of service quality disconfirmation. In addition, community group-buying users with strong time consciousness have higher expectations of product quality to reduce the time spent searching for and processing product quality information to efficiently confirm product quality, which leads to greater product quality disconfirmation. Therefore, the following hypotheses are proposed:
H5a: The impact of perceived price on service quality disconfirmation in community group-buying is strengthened by time consciousness.
H5b: The impact of perceived price on product quality disconfirmation in community group-buying is strengthened by time consciousness.
Based on the hypotheses discussed above, we construct our research model, which reveals the influencing mechanism that underlies community group-buying users’ discontinuous use intention affected by the anti-monopoly of platform economy. The proposed model is presented in Fig.1, and its core concepts are summarized in Table 2. The potential impacts of users’ gender, age, education, income, and average monthly use frequency are controlled.
Figure 1 The Research Model
Table 2 Constructs and definitions
04
Methods
4.1 Scenario-based survey design
A scenario-based questionnaire is a survey method that determines respondents’ decisions by referring to their responses to a range of scenarios, which can provide more details and ensure the veracity of these responses[50]. This approach provides more scenarios and details to help participants engage in decision-making scenarios and provide more realistic and credible responses[51]. Therefore, we adopted a scenario-based questionnaire to help the subjects recall and better understand the background of the anti-monopoly of platform economy and thus offer more credible judgments.
This questionnaire includes two parts. The first part is the participants’ demographic characteristics. The second part is the measurement of the constructs. First, we use several examples to help the participants better understand the policy background. Subsequently, six scenarios are established. The first scenario is used to measure the participants’ perceived price, as shown in Fig. 2. The second scenario is used to measure product quality disconfirmation and service quality disconfirmation by noting that while red envelope subsidies, ultralow-priced products, and discounts are being reduced, the products and services remain the same. In the third scenario, which is designed to measure price sensitivity, we highlight that due to the release of the Anti-monopoly Guidelines of Platform Economy, red envelope subsidies, ultralow-priced products, and discounts are decreasing on community group-buying platforms. The fourth scenario explains using the community group can save time and effort to better measure time consciousness. Finally, the specific expressions in the fifth and sixth scenarios are the same as those in the third scenario and are used to measure perceived dissatisfaction and users’ discontinuous intention, respectively.
Figure 2 A Part of the Scenario-based Survey
4.2 Measurement
All items are measured with the five-point Likert scale, from 1 = “completely agree” to 5 = “completely disagree”. As shown in the appendix, perceived dissatisfaction and discontinuance intention are measured via four items proposed by Wu et al.[7]. Product quality disconfirmation and service quality disconfirmation are operationalized via three items proposed by Wang et al.[42] and Qazi et al.[36]. Perceived price using three items are modified from a study by Wang et al.[42].Price sensitivity is measured according to three items developed and verified by Natarajan et al.[44]. Finally, time consciousness is measured by four items obtained from Chang et al.[47] and Kleijnen et al.[48].
To guarantee the quality of the questionnaire and our ability to successfully administer the survey in China, the questionnaire was first designed in English and then rewritten in Chinese. Regarding reliability, all the items were rewritten in Chinese by two individuals with overseas study experience. Subsequently, Chinese professional translators confirmed the veracity of the English version by comparing it to the two Chinese versions. When any controversy appeared, all researchers discussed the approach to translation until a consensus was reached. We also completed a pretest involving 20 participants prior to administering the formal questionnaire. According to the results of this pretest, we improved the expression of the items related to time consciousness.
4.3 Sample and data
This questionnaire was distributed from April 10, 2021, to April 29, 2021. We used the snowball sampling method, a recommendation-based method. Therefore, we designed a message to send to users with experience in community group-buying (the target group) through Wenjuanxing (a professional online survey platform in China), WeChat, QQ, and e-mail. As an incentive, each valid participant received a 5 RMB reward. To ensure data quality, each participant was required to read the background description before answering and completing all the questions to prevent missing values. Participants with the same IP address or account were allowed to complete the questionnaire only once. Responses that took less than 250 seconds or more than 1,000 seconds to complete were eliminated. 542 valid responses were thus ultimately obtained, and the effective response rate was over 50%.
As shown in Table 3, 67% of participants were female, and 83% were between 20 and 39 years old.Participants mainly used Meituan Youxuan (78.4%). According to a report by a leading industrial service platform, the majority of community group-buying users are females aged 25-49 years, the proportion of users under the age of 29 has shown a clear upward trend, and Meituan Youxuan has a relatively large set of users[52]. Thus, the distributions of gender, age, and most used platforms in our sample were similar to those listed in the above report. Participants mainly used community group-buying 1-8 times a month (92.4%) and bought vegetables (59.6%) and fruits. These results are consistent with the report which stated that over 50% of users mainly bought fresh fruits and vegetables, and 76% used this form of shopping less than 8 times a month[53]. In addition, 82.1% of the participants had a university education, and 54.8% earned more than 2,000 yuan a month. These factors might be related to the characteristics of our sample location (our sample was drawn from third-tier cities or below and places close to a university).
Table 3 Sample characteristics (N=542)
4.4 PLS-SEM data analysis
SmartPLS 3 software was used for analysis. PLS-SEM can relax the normality distribution assumption, which is required by CB-SEM (covariance-based SEM), and has minimum requirements for sample size, measurement scale, and residual distribution[54,55]. PLS-SEM can also test more complex models with relatively small sample sizes. The main reasons for adopting PLS-SEM are summarized as follows. a. The research objective is to extend existing theories, which is exploratory. b. The analysis is for the purpose of prediction. c. The model is comparatively complex. d. The sample size is small. e. The data does not follow a normal distribution.
4.5 Common method bias and nonresponse bias
We tested for common method bias. First, we used the Harman one-factor test[57] to test each construct. According to the outcomes of our principal component factor analysis, the total covariance interpretational level of the seven constructs reached 71.4%, with the highest interpretational level of a single factor being 27.9% (the single factor covariance interpretation levels ranged from 4.12% to 7.85%), which did not exceed 50%[57]. Accordingly, no single factor could explain all the indicators. Second, the marker variable method was used [56,57,58]. Results showed that label variables didn’t have significant effects on the perceived price, product quality disconfirmation, service quality disconfirmation, price sensitivity, time consciousness, perceived dissatisfaction, and discontinuous use intention. Therefore, there was no significant concern regarding common method bias.
We also tested for nonresponse bias.Armstrong and Overton[59] point out that compared with early responders, late responders are more likely to be nonresponders. Thus, the subjects who answered in the first half of the questionnaire collection process were classified as early responders, while those who responded in the second half were classified as late responders. Accordingly, there were 219 early responders and 323 late responders. Moreover, the gender and age did not differ significantly between these two groups. Therefore, nonresponse bias was ruled out.
05
Results
5.1 Measurement model assessment
The reliability and convergent and discriminant validity of each construct were examined. As presented in Table 4, the Cronbach’s alpha coefficients of each construct ranged from 0.820 to 0.917, and the lowest composite reliability (CR) value was 0.889 and the highest was 0.941, which were above the threshold (α≥0.7[60], CR≥0.8[61]). Thus, the reliability of the model was acceptable. The minimum average variance extraction (AVE) value of each construct was 0.667 (ranging from 0.667 to 0.800), which exceeded the threshold level of 0.5[62]. The factor loadings of all items were higher than 0.7, which ranged from 0.729 to 0.923. All factors were significantly related to the corresponding constructs (p<0.001)[63]; therefore, convergent validity was supported. The results shown in Table 5 also indicated that AVE square root outweighed the correlation coefficient of each construct[62]. Discriminant validity was also measured by calculating heterotrait-monotrait ratios (HTMTs). As shown in Table 6, all HTMT ratios were below 0.9[64]; thus, discriminant validity was supported. In the multicollinearity test, all potential variables have variance expansion factor (VIF) values between 1.039 and 1.252, less than 3[54].
Table 4 Convergent validity
Table 5 Discriminant validity: Fornell-Larcker criterion
Table 6 Discriminant validity: Heterotrait-monotrait (HTMT)
5.2 Model fit
In this study, we tested the values of the standardized root mean square residual (SRMR) and the normed fit index (NFI) to assess how well the model fits the sample data. As a vital model fit evaluation index, the SRMR value is helpful in determining whether a model has been developed incorrectly. The SRMR value was 0.067, which was lower than the threshold value of 0.08[64], indicating that the model fits the research data well. In addition, the NFI value was 0.805, higher than 0.7, indicating that our model and data were well matched[65].
5.3 Structural model assessment
We used the Bollen-Stine bootstrap procedure through 5000 random samplings. The results are shown in Fig. 3 and Table 7. These results showed 38% variance for users’ discontinuous intention, 18.2% variance for perceived dissatisfaction, 29.7% variance for product quality disconfirmation, and 18% variance for service quality disconfirmation. There was a significant correlation between dissatisfaction and discontinuance intention (β=0.618, P<0.001). Specifically, when the level of dissatisfaction is higher, the level of discontinuance intention is higher, which supports H1. Product quality disconfirmation was significantly correlated with dissatisfaction (β=0.187, p<0.001). When the degree of product quality disconfirmation is higher, the degree of dissatisfaction is higher, supporting H2a. Service quality disconfirmation was significantly correlated with dissatisfaction (β=0.287, p<0.001). When the degree of service quality disconfirmation is higher, the degree of dissatisfaction is higher; therefore, H2b is supported. Perceived price and product quality disconfirmation were significantly correlated (β=0.452, p<0.001). When the level of the perceived price is higher, the level of product quality disconfirmation is higher, which supports H3a. Perceived price was significantly correlated with service quality disconfirmation (β=0.319, p<0.001). When the level of perceived price is higher, the level of service quality disconfirmation is higher, which supports H3b. We also tested the control variables, which had no distinct effect on discontinuance use intention.
Figure 3 PLS-SEM estimation of the path model
Table 7 Causal relationships
5.4 Importance-performance map analysis(IPMA)
IPMA takes the performance of each construct into consideration, which is a supplement of PLS-SEM results. Each construct has a performance score between 0 and 100[46]. For a particular criterion construct, IPMA compares the total effect (importance) of the structural model with the average of the potential variable scores (performance) to emphasize important areas (or specific areas of focus for the model) to improve management activities[66].
As shown in Fig. 4, the construct total effect of perceived dissatisfaction (PD) on discontinuance use intention (DUI) was 0.618. The construct performance of PD affecting DUI was 33.091. Due to its high importance, PD was thus highly correlated with increasing DUI. However, the low performance of PD indicates great potential for improvement. In addition, as shown in Fig. 5, the construct total effects of product quality disconfirmation (PQD) and service quality disconfirmation (SQD) on PD were 0.187 and 0.287, respectively. The construct performances of PQD and SQD affecting PD were 24.714 and 22.068, respectively. SQD was relatively more important than PQD in affecting PD. Nevertheless, the performance of both factors was relatively low, that is, these factors are major areas for improvement.
Figure 4 Importance-performance map analysis of DUI
Figure 5 Importance-performance map analysis of PD
5.5 Moderation analysis
The simple slope shown in Fig. 6a demonstrates that price sensitivity moderates the impact of perceived price on product quality disconfirmation. Hence, when price sensitivity is high, the positive correlation between perceived price and product quality disconfirmation is strengthened; when price sensitivity is low, it is weakened. Fig. 6b shows that when price sensitivity is high, perceived price is more likely to result in service quality disconfirmation. Fig. 7a shows that when time consciousness is higher, the positive correlation between perceived price and quality of service disconfirmation is stronger. Finally, Fig. 7b shows that when time consciousness is high, perceived price is more likely to result in product quality disconfirmation.
Figure 6 Price Sensitivity as a Moderator
Figure 7 Time Consciousness as a Moderator
To determine whether these moderating effects are significant, we employed the bootstrapping method. As shown in Table 7, price sensitivity significantly moderates the influence of perceived price on product quality disconfirmation (β=0.166, p<0.001); H4a is confirmed. Price sensitivity, however, does not moderate the effect of perceived price on service quality disconfirmation (β=0.095, p>0.05); thus, H4b is not confirmed. Time consciousness does not play a moderate role in the impact of perceived price on service quality disconfirmation (β=0.079, p>0.08) and product quality disconfirmation (β=0.053, p>0.1); H5a and H5b are not supported.
5.6 Predictive relevance
We also used a nonparametric test method—the Stone-Geisser test. The Q2 value was calculated using the blindfolding process to test the predictive correlation of endogenous latent constructs[67]. The Q2 values of the four endogenous latent constructs were all higher than 0 (0.223 for product quality disconfirmation, 0.136 for service quality disconfirmation, 0.132 for dissatisfaction, and 0.253 for discontinuous use intention), passing the test. These results support the predictive relevance of our model for endogenous potential variables[68].
06
Discussion and conclusion
This study proposed a model for the community group-buying user’ discontinuance intention affected by the anti-monopoly of platform economy from the perspective of perceived price and EDT. The results show that perceived price positively affects product quality disconfirmation and service quality disconfirmation, which, in turn, increases dissatisfaction and decreases use intention. Users with high price sensitivity exhibit greater product quality disconfirmation, but price sensitivity does not moderate the effect of perceived price on service quality disconfirmation. Furthermore, time consciousness does not moderate the influence of perceived price on service quality disconfirmation and product quality disconfirmation.
First, our results show that product quality disconfirmation and service quality disconfirmation are crucial to dissatisfaction, service quality disconfirmation plays a greater role, and dissatisfaction is a predictor of discontinuance intention, supporting H1, H2a, and H2b. Specifically, the greater the product and service quality disconfirmation, the stronger the dissatisfaction and the discontinuance intention. Previous literature mainly focuses on product quality disconfirmation, while research on service quality disconfirmation remains relatively limited. Although Abrate et al.[10] have also focused on service quality disconfirmation, they do not distinguish product quality disconfirmation from service quality disconfirmation. This study shows that in community group-buying, service quality disconfirmation plays a greater role in dissatisfaction than product quality disconfirmation. This may be attributed to the fact that community group-buying in this study mainly involved fresh fruit, which has relatively high service requirements[34].
Second, we find that perceived price dramatically affects both product and service quality disconfirmation, supporting H3a and H3b. That is, the higher the perceived price, the higher the degree of product and service quality disconfirmation. This conclusion is in line with Abrate et al.[10], who propose that when the price of a hotel is high, consumers’ expectations rise and that these high expectations are conducive to negative disconfirmation. However, these authors perform only qualitative analysis without any empirical test. In this paper, we adopt an empirical test to confirm this point of view considering the anti-monopoly of platform economy.
Third, our results confirm that price sensitivity significantly moderates the effect of perceived price on product quality disconfirmation, supporting H4a. Specifically, when perceived prices rise, users with high price sensitivity develop higher requirements for product quality and service quality disconfirmation. Wu et al.[7] have found that users with high price sensitivity are more responsive to price changes and tend to focus on experiences of value. Therefore, our results extend those of Wu et al.[7]. Moreover, we find that price sensitivity does not play a moderating role between perceived price and service quality disconfirmation, whereby H4b is rejected. This contrasts with Chua et al.[45], who indicate that vacationers with high price sensitivity are critical when evaluating experiences of value. This difference may be related to the “order today, arrive tomorrow” logistics service provided by community group-buying platforms, which is a great advantage over other shopping platforms[34]. Especially amid COVID-19, this “no-contact” and effective purchasing method provides convenience for users, better satisfying their needs and enhancing their perceived value[34].
Fourth, our results show that time consciousness does not play a moderating role in the impact of perceived price on service quality disconfirmation and product quality disconfirmation. H5a and H5b are thus rejected, in contrast to Kleijnen et al.[48] who indicate that consumers with strong time consciousness pursue fast and convenient services and hope to obtain time-related benefits. The reasons for this inconsistency may be twofold. First, users with strong time consciousness may have a plan for their work[48], and the logistical delivery service of “order today, arrive tomorrow”[34] may help them form better plans. Thus, they do not necessarily experience a greater degree of service quality disconfirmation. In contrast, users with weak time consciousness are less inclined to engage in planning[48] and therefore have higher expectations regarding the flexibility of logistical delivery services, as well as higher requirements for service quality. Second, community group-buying platforms focus on daily necessities[69]. Since the quality information for these items is relatively easy and quick to process, it is unlikely to affect shopping efficiency. Thus, users with strong time consciousness may not experience greater product quality disconfirmation.
6.1 Theoretical implications
First, this study contributes to the literature on mobile users’ discontinuance intentions. Previous literature considered online user behavior mainly from the perspective of the motivation of information system users[15,22], ignoring the impact of government policies on users’ discontinuous use behavior. Given that red envelope subsidies, ultralow-priced products, and product discounts are expected to gradually decrease because of the anti-monopoly of platform economy, this study constructs a theoretical model from the perspective of perceived price and disconfirmation. The results of empirical analysis indicate that users’ expectations of product quality and service quality increase with perceived price, which may lead to disconfirmation, dissatisfaction, and discontinuance intention.
Second, we extend EDT in several ways. First, by combining the perspective of perceived price, we demonstrate that an increase in perceived price results in higher product quality disconfirmation and service quality disconfirmation. Second, considering the moderating effects of price sensitivity, we find that for users with high price sensitivity, the increase in perceived price leads to greater product quality expectation disconfirmation, but not to greater service quality disconfirmation. Therefore, it is necessary to divide disconfirmation into product quality disconfirmation and service quality disconfirmation. Third, we find that time consciousness does not have a significant moderating effect on the relationship between perceived price and service quality disconfirmation, which suggests that community group-buying users with strong time consciousness do not blindly pursue service quality. This finding is in contrast to that of Kleijnen et al.[48]and Belanche et al.[49], who maintain that consumers with high levels of time consciousness pursue swift and convenient services.
Third, our study sheds new light on the literature on platform governance. Previous research on platform governance mainly studied from the perspectives of fairness, technology, and information, while ignoring the role of online users. Based on the perceived price and EDT, this paper finds that an increase in users' perceived price leads to higher product quality disconfirmation and service quality disconfirmation, which results in dissatisfaction and discontinuance intention. This discovery reveals that the anti-monopoly of platform economy can achieve the goal of survival of the fittest by influencing users’ behavior.
6.2 Practical implications
This research also provides insightful managerial implications for community group-buying platform merchants, managers, and regulators.
Community group-buying merchants should take steps to improve product quality and to be more cautious when instituting promotional activities. Prior to the promulgation of the anti-monopoly policy of platform economy, due to the low prices and convenience of community group-buying, users had relatively low expectations regarding product quality. Even if the quality of a product was generally unsatisfactory, users might continue to buy it. However, affected by the anti-monopoly of platform economy, merchants can no longer sell below their costs. As red envelope subsidies, ultralow-priced products, and product discounts continue to decrease, users experience a higher perceived price and develop higher expectations regarding product quality. Therefore, if product or service quality is not effectively improved, users can become dissatisfied and discontinue using community group-buying platforms. Furthermore, merchants must be more cautious when instituting promotional activities, and it is very important to maintain prices within a reasonable range. According to our results, users’ expectations increase as their perceived price rises, resulting in greater disconfirmation. Although consumers are willing to participate in sales promotions and purchase products, their dissatisfaction markedly increases once the original product price is restored.
In addition, community group-buying platform managers should strictly control product quality and improve service quality. Our results indicate that the red envelope subsidies, ultralow-priced products, and product discounts provided by platforms have gradually decreased, and that users’ perceived price has risen accordingly, leading to their higher expectations regarding products and services. If these expectations are not met, these users will become dissatisfied, which will result in their discontinuance intention. Moreover, platform managers should focus more on improving the efficiency of logistical distribution and providing more sincere customer service and more stringent privacy protection services, which are even more important factors. For example, platform managers should strive to upgrade their delivery service from “order today, arrive tomorrow” to “order today, arrive today”.
Finally, for community group-buying regulators, the anti-monopoly of platform economy should be resolutely implemented. Affected by this policy, the increase in perceived price causes community group-buying users to exhibit discontinuance intention, which leads to the loss of platform users and business closure. However, according to this study, consumers become dissatisfied and stop using a platform when they perceive an increase in price without a corresponding increase in the quality of the platform's products or services. This dynamic emphasizes the need for platform managers to constantly improve their service quality and strengthen the supervision and control of their product quality so that platform merchants can constantly improve product quality, thereby promoting the sustainable development of their community group-buying platform.
6.3 Limitations and future research directions
This study also has several limitations. First, we have found that perceived price affected by the anti-monopoly of platform economy has an effect on discontinuance intention. The anti-monopoly of platform economy also affects other psychological factors among users. Therefore, future research could investigate these impacts from additional perspectives.
Second, although we find that disconfirmation can be divided into product and service quality disconfirmation, future research could measure disconfirmation with respect to other dimensions, for example, users’ disconfirmation of product diversity.
Third, although the scenario-based survey was designed to encourage participants to answer the questions as well as possible, the results of our study also have some limitations. Future research could therefore conduct an empirical analysis of data related to community group-buying platforms (such as Meituan Youxuan and Dduoduo Maicai) to validate our research results.
Fourth, the leader of a community group-buying team (typically a local business) also plays an important role. Affected by the anti-monopoly of platform economy, consumers’ perceptions of government regulation are also worth considering. These perspectives could be considered in future studies.
Fifth, the research data in this paper were collected from Chinese community group-buying users. Therefore, whether these results can be applied to other countries and cultures requires further testing. Future studies could thus examine whether different effects can be observed in the context of other countries and cultures considering the anti-monopoly of platform economy.
Disclosure statement
No competing economic interests would affect the work reported in this article.
参 考 文 献
[1] 网经社. 《2021年度中国社区团购市场数据报告》[R/OL]. [2022-07-02]. http://www.100ec.cn/index/detail--6608043.html.
[2] 国务院反垄断委员会. 《国务院反垄断委员会关于平台经济领域的反垄断指南》[Z/OL]. [2021-07-02]. http://www.gov.cn/xinwen/2021-02/07/content_5585758.htm.
[3] 第一财经. 一年烧掉上千亿,社区团购退场玩家过半[Z/OL]. [2022-11-07]. https://baijiahao.baidu.com/s?id=1721917077586526993&wfr=spider&for=pc.
[4] Luqman A, Masood A, Weng Q, et al. Linking excessive SNS use, technological friction, strain, and discontinuance: The moderating role of guilt[J]. Information Systems Management, 2020, 37(2): 94-112.
[5] Fu S, Li H, Liu Y. Why discontinue Facebook usage? An empirical investigation based on a push-pull-mooring framework[J]. Industrial Management & Data Systems, 2021, 121(11): 2318-2337.
[6] Chen J V, Tran A, Nguyen T. Understanding the discontinuance behavior of mobile shoppers as a consequence of technostress: An application of the stress-coping theory[J]. Computers in Human Behavior, 2019, 95: 83-93.
[7] Wu C, Kao S C, Chiu H Y. Determinants of discontinuous intention of attention to mobile instant message services[J]. Journal of Retailing and Consumer Services, 2019, 49: 219-230.
[8] Huang J, Zhou L. Social gamification affordances in the green IT services: Perspectives from recognition and social overload[J]. Internet Research, 2020, 31(2): 737-761.
[9] Kim D, Park K, Lee D J, et al. Predicting mobile trading system discontinuance: The role of attention[J]. Electronic Commerce Research and Applications, 2020, 44: 101008.
[10]Abrate G, Quinton S, Pera R. The relationship between price paid and hotel review ratings: Expectancy-disconfirmation or placebo effect?[J]. Tourism Management, 2021, 85: 104314.
[11]Oliver R L. A cognitive model of the antecedents and consequences of satisfaction decisions[J]. Journal of Marketing Research, 1980, 17(4): 460-469.
[12]Zhou Z, Li X, Jin X L. Enablers and inhibitors of discontinuous use in social networking sites: A study on Weibo[C/OL]//The 22nd Pacific Asia Conference on Information Systems(2018), Yokohama, Japan. AIS, 2018: 179.
[13]Lin J, Lin S, Turel O, et al. The buffering effect of flow experience on the relationship between overload and social media users’ discontinuance intentions[J]. Telematics and Informatics, 2020, 49: 101374.
[14]Luqman A, Masood A, Ali A. An SDT and TPB-based integrated approach to explore the role of autonomous and controlled motivations in “SNS discontinuance intention”[J]. Computers in Human Behavior, 2018, 85: 298-307.
[15]Cao X, Sun J. Exploring the effect of overload on the discontinuous intention of social media users: An S-O-R perspective[J]. Computers in Human Behavior, 2018, 81: 10-18.
[16]Tang Z, Chen L, Gillenson M L. Understanding brand fan page followers’ discontinuance motivations: A mixed-method study[J]. Information & Management, 2019, 56(1): 94-108.
[17]Lo J. Exploring the buffer effect of receiving social support on lonely and emotionally unstable social networking users[J]. Computers in Human Behavior, 2019, 90: 103-116.
[18]Islam T, Li J, Ali A, et al. Mapping online App hate: Determinants and consequences[J]. Telematics and Informatics, 2020, 51: 101401.
[19]Wang J, Zheng B, Liu H, et al. A two-factor theoretical model of social media discontinuance: Role of regret, inertia, and their antecedents[J]. Information Technology & People, 2020, 34(1): 1-24.
[20]Fan X, Jiang X, Deng N, et al. Does role conflict influence discontinuous usage intentions? Privacy concerns, social media fatigue and self-esteem[J]. Information Technology & People, 2020, 34: 1152-1174.
[21]Kuo R Z. Why do people switch mobile payment service platforms? An empirical study in Taiwan[J]. Technology in Society, 2020, 62: 101312.
[22]Xie X Z, Tsai N C. The effects of negative information-related incidents on social media discontinuance intention: Evidence from SEM and fsQCA[J]. Telematics and Informatics, 2021, 56: 101503.
[23]Lin S, Lin J, Luo X R, et al. Juxtaposed effect of social media overload on discontinuous usage intention: The perspective of stress coping strategies[J]. Information Processing & Management, 2021, 58(1): 102419.
[24]Soroya S H, Farooq A, Mahmood K, et al. From information seeking to information avoidance: Understanding the health information behavior during a global health crisis[J]. Information Processing & Management, 2021, 58(2): 102440.
[25]Darban M, Kim M, Koksal A. When the technology abandonment intentions remitted: The case of herd behavior[J]. Information Technology and Management, 2021, 22(3): 163-178.
[26]Liébana-Cabanillas F, Singh N, Kalinic Z, et al. Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: A multi-analytical approach[J]. Information Technology and Management, 2021, 22(2): 133-161.
[27]甘春梅,林晶晶,肖晨.扎根理论视角下微信用户间歇性中辍行为的探索性研究[J].信息资源管理学报,2021,11(5):96-102,113.
[28]Huang C K, Lee N C A, Chen W C. Dilemmatic dual-factor determinants of discontinuous intention in cryptocurrency usage[J]. Information Technology & People, 2023, 36(2): 564-594.
[29]Sun J, Lee S K. Flooded with too many messages? Predictors and consequences of instant messaging fatigue[J]. Information Technology & People, 2022, 35(7): 2026-2042.
[30]Pang H, Ruan Y. Determining influences of information irrelevance, information overload and communication overload on WeChat discontinuance intention: The moderating role of exhaustion[J]. Journal of Retailing and Consumer Services, 2023, 72: 103289.
[31]Wang W T, Wang Y S, Liu E R. The stickiness intention of group-buying websites: The integration of the commitment–trust theory and e-commerce success model[J]. Information & Management, 2016, 53(5): 625-642.
[32]Klein A, Sharma V M. Consumer decision-making styles, involvement, and the intention to participate in online group buying[J]. Journal of Retailing and Consumer Services, 2022, 64: 102808.
[33]Chou H Y. Units of time do matter: How countdown time units affect consumers’ intentions to participate in group-buying offers[J]. Electronic Commerce Research and Applications, 2019, 35: 100839.
[34]Li J, Li B, Shen Y, et al. Study on the steady state of the propagation model of consumers’ perceived service quality in the community group-buying[J]. Journal of Retailing and Consumer Services, 2022, 65: 102882.
[35]Sun S, Zhang B. Operation strategies for nanostore in community group buying[J]. Omega, 2022, 110: 102636.
[36]Qazi A, Tamjidyamcholo A, Raj R G, et al. Assessing consumers’ satisfaction and expectations through online opinions: Expectation and disconfirmation approach[J]. Computers in Human Behavior, 2017, 75: 450-460.
[37]Yi Y. A critical review of consumer satisfaction[J]. Review of Marketing, 1990, 4(1): 68-123.
[38]Cai R, Chi C G Q. Pictures vs. reality: Roles of disconfirmation magnitude, disconfirmation sensitivity, and branding[J]. International Journal of Hospitality Management, 2021, 98: 103040.
[39]Zhang L, Wei W, Line N D, et al. When positive reviews backfire: The effect of review dispersion and expectation disconfirmation on Airbnb guests’ experiences[J]. International Journal of Hospitality Management, 2021, 96: 102979.
[40]Bai X, Marsden J R, Ross Jr W T, et al. A note on the impact of daily deals on local retailers’ online reputation: Mediation effects of the consumer experience[J]. Information Systems Research, 2020, 31(4): 1132-1143.
[41]Calvo-Porral C, Lévy-Mangin J P. Store brands’ purchase intention: Examining the role of perceived quality[J]. European Research on Management and Business Economics, 2017, 23(2): 90-95.
[42]Wang Y S, Tseng T H, Wang W T, et al. Developing and validating a mobile catering app success model[J]. International Journal of Hospitality Management, 2019, 77: 19-30.
[43]艾瑞咨询. 《2021年社区团购NPS用户体验研究报告》 [R/OL]. 2021 [2022-9-18]. http://www.100ec.cn/detail--6601541.html
[44]Natarajan T, Balasubramanian S A, Kasilingam D L. Understanding the intention to use mobile shopping applications and its influence on price sensitivity[J]. Journal of Retailing and Consumer Services, 2017, 37: 8-22.
[45]Chua B L, Lee S, Goh B, et al. Impacts of cruise service quality and price on vacationers’ cruise experience: Moderating role of price sensitivity[J]. International Journal of Hospitality Management, 2015, 44: 131-145.
[46]Lee H, Lalwani A K, Wang J J. Price no object!: The impact of power distance belief on consumers’ price sensitivity[J]. Journal of Marketing, 2020, 84(6): 113-129.
[47]Chang H H, Fu C S, Fang P W, et al. The effects of relationship maintenance and relationship investment on self-service technology relationship performance[J]. Information Technology & People, 2016, 29(3): 496-526.
[48]Kleijnen M, De Ruyter K, Wetzels M. An assessment of value creation in mobile service delivery and the moderating role of time consciousness[J]. Journal of Retailing, 2007, 83(1): 33-46.
[49]Belanche D, Casaló L V, Flavián C, et al. Trust transfer in the continued usage of public e-services[J]. Information & Management, 2014, 51(6): 627-640.
[50]Siponen M, Vance A. Neutralization: New insights into the problem of employee systems security policy violations[J]. MIS Quarterly, 201034(3): 487-502.
[51]Atzmüller C, Steiner P M. Experimental vignette studies in survey research[J]. Methodology, 2010, 6(3): 128-138.
[52]网易网. 《2020-2021中国社区团购行业研究报告》[R/OL]. [2022-9-18]. https://www.163.com/dy/article/GE5NLR790511ANPT.html.
[53]艾瑞咨询. 《2020上半年中国社区团购行业专题研究报告》[R/OL]. [2022-9-18]. https://www.sohu.com/a/417737916_533924.
[54]Hair J F, Risher J J, Sarstedt M, et al. When to use and how to report the results of PLS-SEM[J]. European Business Review, 2019, 31(1): 2-24.
[55]Shiau W L, Sarstedt M, Hair J F. Internet research using partial least squares structural equation modeling (PLS-SEM)[J]. Internet Research, 2019, 29(3): 398-406.
[56]Shiau W L, Yuan Y, Pu X, et al. Understanding Fintech continuance: Perspectives from self-efficacy and ECT-IS theories[J]. Industrial Management & Data Systems, 2020, 120(9): 1659-1689.
[57]Podsakoff P M, Organ D W. Self-reports in organizational research: Problems and prospects[J]. Journal of Management, 1986, 12(4): 531-544.
[58]Chin W W, Thatcher J B, Wright R T. Assessing common method bias: Problems with the ULMC technique[J]. MIS Quarterly, 2012, 36(3): 1003-1019.
[59]Armstrong J S, Overton T S. Estimating nonresponse bias in mail surveys[J]. Journal of Marketing Research, 1977, 14(3): 396-402.
[60]Chin W W, Gopal A. Adoption intention in GSS: Relative importance of beliefs[J]. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 1995, 26(2-3): 42-64.
[61]Nunnally J. Psychometric methods[M]. New York: McGraw Hill New Yor, 1978: 464-465.
[62]Fornell C, Larcker D F. Evaluating structural equation models with unobservable variables and measurement error[J]. Journal of Marketing Research, 1981, 18(1): 39-50.
[63]Bock G W, Zmud R W, Kim Y G, et al. Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological factors, and organizational climate[J]. MIS Quarterly, 2005, 29(1): 87-111.
[64]Henseler J, Ringle C M, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling[J]. Journal of the Academy of Marketing Science, 2015, 43(1): 115-135.
[65]Rasoolimanesh S M, Roldán J L, Jaafar M, et al. Factors influencing residents’ perceptions toward tourism development: Differences across rural and urban world heritage sites[J]. Journal of Travel Research, 2017, 56(6): 760-775.
[66]Schloderer M P, Sarstedt M, Ringle C M. The relevance of reputation in the nonprofit sector: The moderating effect of socio-demographic characteristics[J]. International Journal of Nonprofit and Voluntary Sector Marketing, 2014, 19(2): 110-126.
[67]Geisser S. A predictive approach to the random effect model[J]. Biometrika, 1974, 61(1): 101-107.
[68]Hair J F, Hult G T M, Ringle C, et al. A primer on partial least squares structural equation modeling (PLS-SEM) [M]. Los Angeles: Sage Publications, 2016.
[69]Weinswig D. The battle for China’s community group buying market[Z/OL]. [2021-9-18]. https://technode.com/2020/07/28/the-battle-for-chinas-community-group-buying-market/.
收稿日期:2022-11-16
Appendix: Constructs and items
作者简介
刘启华,教授,博士生导师,研究方向为在线消费者行为和电子商务;
彭思婕,硕士生,研究方向为在线消费者行为;
许立扬,博士生,研究方向为在线消费者行为;
周婧怡,博士后,研究方向为在线消费者行为,Email:704573394@qq.com。
*原文载于《信息资源管理学报》2023年第3期,欢迎个人转发,公众号转载请联系后台。
* 引用格式
刘启华,彭思婕,许立扬,等.平台经济反垄断对社区团购用户不持续使用意愿的影响:基于感知价格和期望不一致的视角[J].信息资源管理学报,2023,13(3):39-60.
往期 · 推荐
当期目录 · 专刊 | 2023年第3期 “面向信息管理与信息系统的研究方法应用与实践”
当期荐读 2023年第3期 | 平台隐私保护机制对消费者隐私信息披露的影响
当期荐读 2023年第3期 | “面向信息管理与信息系统的研究方法应用与实践”专刊前言
▲点击访问信息资源管理学报小程序
制版编辑 | 王伊杨
审核 | 于阿媛
长按识别二维码关注我们
信息资源管理学报
微信号
xxzyglxb
分享、在看与点赞
只要你点,我们就是朋友😊