1. Introduction
Sustainability is becoming an increasingly important consideration in various aspects of business. With regard to logistics, recent studies show that much can be done to protect the planet by considering the efficient use of resources [
1,
2,
3,
4]. E-commerce and logistics are inseparable. Purchases made online must be shipped via the road, rail, waterway, or air. In addition to the logistics industry, online stores and home shopping channels increase traffic and affect customer convenience and reliability (and price). Customers can choose an environmentally friendly mode of delivery of goods. Shopping is already related to logistics challenges and storage, and, although all the factors that play a role cannot be listed, online retailers are certainly aware that logistics and sustainability are scientific. However, the significance of e-commerce lies in the sensitivity of stakeholders to responsibilities that go beyond the product and the company. Sustainable logistics is related to CO
2 savings. However, it also extends naturally to social and societal concerns.
Sustainability has also been gaining prominence in academic research on the supply chains owing to the extended supply chains in modern business operations. This field is one of many areas that have recently attracted attention from both scholars and practitioners. The development of the sustainable supply chain in practice has motivated scholars’ investigations. Yang et al. [
5] examined the main perspectives found in research on sustainable retailing in the fashion industry. They found that the most prominent topics in the field are sustainable retailing in disposable fashion, fast fashion, slow fashion, green branding, and eco-labeling; retailing of secondhand fashion; reverse logistics in fashion retailing; and emerging retailing opportunities in e-commerce. This finding implies that research on sustainable retailing in the fashion industry in developing markets is lacking. Oláh et al. [
6] argued that everyone clearly wins by applying sustainability to e-commerce. They claimed that these wins can be achieved by improving and safeguarding the quality of life by protecting the environment, preserving natural resources, and maintaining and sustaining the economy. They also concluded that a sustainable e-commerce environment leads to greater benefits, not only in terms of online business sustainability, but also in terms of policy-making and environmental protection, as companies create economic value and avoid labor unrest. Focusing on cross-border e-commerce in China, Su et al. [
7] analyzed the internal structure and dynamic layout characteristics of sustainable cross-border e-commerce policy documents. Based on their analysis, they argued that governments should focus on supervising payments, transactions, and goods in the early stages of development, and should begin comprehensively supervising all aspects of the cross-border e-commerce supply chain to create a sustainable cross-border e-commerce environment.
Specifically, consumer activism is increasing, and the demand for fast and immediate delivery is growing. Sustainable logistics solutions, such as recycling and reusing delivery packaging, are affordable mechanisms for online businesses to ensure ecofriendly, same-day deliveries that satisfy their customers. Two revolutions in consumer behavior are happening simultaneously. Amazon Logistics has ensured that customers are accustomed to receiving goods within hours of placing an order. In response, businesses seeking to maintain their market share are rushing to develop on-demand delivery options. Although consumers demand that goods be delivered with imperative immediacy, they also seek to influence what brands sell. Consumer activism is increasing, and customers are currently more likely to purchase based on brand beliefs than they were three years ago.
In a recent study on sustainable logistics and e-commerce in Asian markets, Choi and Mai [
8] investigated whether the characteristics of e-service quality positively influenced customer loyalty as one of the sustainable success factors in this growing e-commerce industry, especially in the Vietnamese market. They argued that it is crucial to promote e-trust as a vital element for the sustainable growth of the e-commerce industry. Focusing on the Taiwanese market, Moslehpour et al. [
9] proposed a model that partially combines personality traits and technology acceptance model attributes to study the influences of personality characteristics and perceptions of technology on e-purchase intentions. They found that consciousness significantly influences perceived usefulness, perceived ease of use, and openness to experience. In particular, perceived ease of use had the strongest positive impact on sustainable e-purchase intentions. As in our study, Akram et al. [
10] examined the Chinese market and studied the impacts of situational variables, scarcity and serendipity, on online impulse buying in the Chinese social commerce environment. The results confirmed that these situational factors positively influence online impulse buying among Chinese online shoppers in this environment. Given the growing significance of sustainable logistics, this study investigates the impact of the quality of logistics services related to online shopping on customer satisfaction and in driving subsequent repeat purchasing behavior in China.
1.1. Research Background and Objectives
The first e-commerce site was launched in China in 1998. Thereafter, online shopping malls experienced rapid growth, both quantitively and qualitatively. The business-to-consumer (B2C) online shopping mall “8848” launched the first Chinese website, marking the beginning of online shopping in the country. The development process of online shopping in China can be divided into three stages.
During the first stage, the number of Chinese Internet users was comparatively small relative to today. According to statistics issued in 2000 by China, there were only ten million Internet users. At the time, 8848 was the benchmark for online shopping malls. During this period, most Internet users primarily used e-mail, and Internet use was generally limited to reading the news. The online shopping market was fledgling during this initial phase, and Internet users were unfamiliar with the concept of shopping using the Internet. This early stage of infrastructure development provided a few online shopping malls, and the industry struggled to grow through the conditions of early development.
Several shopping malls dominated online shopping in China. For example, Taobao (淘宝), Tianmao (天猫), DangDang (当当), and ZhuoYue (卓越) were established during this initial period. With an increase in the digital presence of S&P (Standard and Poor’s) companies and online gaming businesses, the Chinese online communications market was transformed. During this phase, general changes were made to the Chinese e-commerce environment as Internet users began to perceive online purchasing as the next trend in shopping and their numbers increased.
Additionally, businesses began using business-to-business e-commerce to solicit orders and for networking opportunities in China, and the concept of “Internet vendors” was born. With these changes, the online shopping industry in China grew rapidly, thereby accumulating many capital gains.
From late 2009, traditional commerce entered the online environment in earnest, and, with the smooth inflow of capital, the e-commerce environment matured, and online shopping was popularized. In 2010, online shopping constituted 23% of all Internet usage, and the rapid development of the Chinese e-commerce market consequently fostered new enterprise. With the steady growth of the Chinese economy and the expansion of Internet usage, it is expected that this high rate of growth will continue.
Internet coverage has expanded. The number of Internet users exceeded 850 million in 2017, and users accessing the Internet on mobile devices exceeded 750 million. This increase in the proliferation of e-commerce has shown a growth rate two to three times faster than that of real GDP. By 2017, the value of e-commerce transactions exceeded CNY 2.5 billion, which is 1.5 times larger than it was in 2015.
Along with the development, evolution, and proliferation of the Internet, information and communications technology (ICT) is developing rapidly. Unprecedented numbers of transactions are taking place via e-commerce.
Businesses can use the Internet to transcend traditional marketplaces, opening them up to the world. However, the rapidly evolving environment provides new opportunities for business, and understanding online customer behavior is essential to remaining competitive and responsive to market fluctuations.
The unique services of online shopping, and particularly logistics services, should be a differentiating factor that enhances customer satisfaction and, consequently, drives repeat purchases.
Previously, customers transacted by visiting brick-and-mortar department stores, specialty stores, supermarkets, and so forth. The advent of new distribution channels has increased purchase opportunities, and the number of online shoppers is gradually increasing. Online shopping is facilitated by quick searches for information and the remote purchasing of products that are more expensive in offline stores. With the availability of products and services unrestricted by time and space, the online shopping market maintains continuous growth.
However, from a marketing perspective, many aspects of a brick-and-mortar shopping mall are difficult to translate into a recognizable online presence. Differentiating between the quality of services offered by various online shopping malls becomes a challenge, especially given the rapid growth of the online market. Compared to traditional shopping malls, online malls are limited in their understanding of customers’ purchasing behaviors and in determining the perception of their online service. Furthermore, additional problems are arising, including data leaks, the stability of electronic payments, and the safety and security of deliveries.
The Internet has enabled online malls to reinforce their representative global distribution, but the fastest growing online shopping market remains that of China. According to statistics released by China’s 艾瑞咨询, the number of Chinese Internet users reached 668 million in 2016, making it the largest Internet-using country in the world. Included in this figure are 350 million people (48.9% of the total) who purchase online. Trade through online shopping reached RMB 18.5 billion, and the growth rate of e-commerce is faster than that of traditional distribution channels.
The number of online shopping malls entering the Chinese market is increasing annually. Conventional Chinese businesses are transforming their distribution models from offline trading to online shopping mall markets. It is therefore imperative for businesses to ascertain the aspects of online shopping that their customers find appealing and the relationships between their customers’ interests, their satisfaction levels, and their repeat purchasing behaviors.
In summary, businesses need to develop their ability to maintain steady customer relations in line with the rising expectations for quality in online shopping logistics. The cases of customer dissatisfaction resulting from damage related to online purchasing are increasing. Therefore, online malls need to continually improve their logistics services to retain customers.
Although e-commerce studies are actively being conducted in foreign countries, a few studies on online shopping in China exist. This increases the risk of failure for foreign businesses in China, owing to the country’s dissimilar business environment and varying cultural characteristics. E-commerce research conducted in China has been limited to that on account payments, Internet safety, and credit queries. Thus, the need for research on the logistics service quality of online shopping in China is increasing. This study analyzes the influence of logistics services on Chinese customers’ satisfaction levels and their repurchase intentions.
1.2. Research Methodologies and Contents
The objective of this study is to measure the impact of logistics services on customer satisfaction and repurchase intentions in China. Accordingly, it combines both reference and empirical research. First, based on the literature, this study theoretically examines online shopping, its development, logistics service quality, customer satisfaction, and intention to repurchase in China. Through a subsequent analysis, online shopping mall services are categorized based on logistics quality factors. These include the quality of information, quality of order, quality of delivery, quality of customer service, and price of delivery, which constitute the variables under study. The literature guides the establishment of the models for the hypotheses used in this empirical research.
This study posits five hypotheses representing the relationships between customer satisfaction and each logistics service factor: quality of information, quality of order, quality of delivery, price of delivery, and customer service. This study puts forth one additional hypothesis on the effects of these factors on repurchase intention, bringing the total number of hypotheses to six.
The collated data underwent an empirical analysis using SPSS 18.0. To test the reliability of specific data, reliability analyses were performed. To test the hypotheses, a correlation analysis and a regression analysis were performed.
This paper is divided into five sections.
Section 1, the introduction, describes the objectives of this research, the methodologies used, and the contents of the paper.
Section 2 examines theories supporting this study, the online shopping malls used in the research, the status of online shopping in China, the quality of logistics services, and previous literature on logistics service quality. It also organizes the concepts of customer satisfaction and repeat purchasing behavior based on the existing literature.
Section 3 presents the models and research hypotheses.
Section 4 discusses the empirical analysis of the hypotheses based on the collated questionnaires.
Section 5 summarizes the research results and concludes the paper.
1.3. Research Limitations
The limitations of this research are as follows. First, the Internet service infrastructure differs between regions, and the quantity of large-scale logistics businesses is insufficient to represent all of China. Additionally, the specific services provided by each logistics company vary. It is possible that the influences of some factors on logistics service quality are not identified in this research.
Second, the research on customer satisfaction and the logistics services of online shopping malls in China is lacking. Therefore, this research proceeds without sufficient verification of the validity of the literature. Thus, a theoretical and systematic model for integration and analysis should be developed.
Third, this research limited the study subjects to young people living in China, which might yield interpretive errors. Furthermore, owing to the limited geographical range and number of respondents, the sample may not be statistically representative of the population.
Fourth, the respondents to the questionnaire answered from their personal perspectives. Thus, subjective opinions on online shopping may influence the responses to certain questions. Future research should include survey methods (e.g., in-depth interviews) that closely monitor the real-time intentions and actions of respondents, which would help to validate the results.
4. Hypothesis Testing and Analysis Results
4.1. Analysis of Observation Data
This study conducted surveys over two months, from 1 December, 2016 to 31 January, 2017 primarily among young Chinese customers with experience purchasing products online as representatives of electronic commerce. The survey questionnaires are presented in
Supplementary Materials. Additionally, the sample firms were selected from a list of logistics companies registered with the Ministry of Communications of China and the membership list of the China International Freight Forwarders Association. Using these data, this study analyzed the effects of customer satisfaction with a logistics service on customers’ intentions to repurchase in the online shopping environment.
As stated, this study establishes quality of information, quality of order, quality of delivery, price of delivery, and customer service as the independent variables affecting logistics service quality.
In all, 116 of 150 survey questionnaires were returned. The questionnaires with insufficient responses or those deemed invalid were removed, and 103 survey questionnaires were used in the final analysis. The response rate was 68.7%.
Examining the demographic characteristics of the samples used in this research, 56 men (54.37%) and 47 women (45.63%) responded to the questionnaire.
The age distribution of respondents was one person aged below 19 years (0.97%), 71 people aged between 20 and 29 years (68.93%, the largest portion), and 31 people aged between 30 and 39 years (30.1%).
The distribution of education level was 13 people with a high school diploma (12.62%), 16 people currently attending college (15.53%), 70 people with a bachelor’s degree (67.96%), and four people with a post-graduate degree.
Examining the occupations of respondents, 14 people were students (13.59%), and the largest group was office worker, with 70 people. Examining the frequency of online purchasing, 23 people bought once or twice per month (22.33%), 34 people bought three times monthly (33.01%), and those with more than three purchases per month total 44 people (42.72%).
Table 2 shows the statistical characteristics of the respondents.
4.2. Evaluation of Measured Items
4.2.1. Reliability Test
Reliability refers to consistency in results when the same concepts are measured repeatedly with the same or similar measurement tools [
46]. The concept can be described through the characteristics of stability, accuracy, consistency, and dependency. Reliability implies obtaining similar results when the same concepts are measured repeatedly and independently through the same or similar measurement tools [
47]. The techniques employed for measurement include split-half reliability, item analyses, Cronbach’s Alpha, equal measure reliability, and inter-rater reliability. When using criteria composed of various items from a single concept, Cronbach’s Alpha is used to obtain the split-half reliability and yield the average value.
As this study used multiple measurements for the same concept, the Cronbach’s Alpha coefficient was employed to examine the internal consistency of the derived factors. A Cronbach’s Alpha coefficient above 0.6 or 0.7 is said to indicate relatively high reliability [
48].
In this study, all items were found to have coefficients above 0.6. The total degree of reliability is 0.931, and, thus, the measured items are deemed reliable. A summary of the reliability analysis results is presented in
Table 3.
Next, this study conducted a Kaiser-Meyer-Olkin (KMO) test based on Cerny and Kaiser [
49]. A KMO value is obtained by adding the sums of the squares of the correlation coefficients and partial correlation coefficients. In general, it is used to test the efficacy of factor analysis. The greater the partial correlation coefficients without the influence of the third variable are, the lower the KMO value. Correspondingly, the lower the partial correlation coefficients without the influence of the third variable are, the higher the KMO value is. Thus, if the correlation between variables is high, the KMO value is high. The higher the KMO value is, the more commonalities there are between variables, indicating that the conclusions of the factor analysis are appropriate. KMO statistics above 0.7 are statistically significant. Thus, a factor analysis is appropriate.
After performing the factor analysis, the KMO value is 0.833, as presented in
Table 4. The result is statistically significant and appropriate for a factor analysis.
4.2.2. Validity Test
This study analyzed the determinants of logistics service quality through a factor analysis to evaluate the validity of the measurement indices. A factor analysis is conducted when evaluating the validity of the determinants of each distinct concept. Additionally, the research evaluates the representation of the tested factors in the original concepts.
The factor analysis uses a varimax rotation of principal components. The factors selected are those with eigenvalues above one, and each factor with a load value above 0.5 is deemed statistically significant.
In the model, the seven extracted factors that affect logistics quality are quality of information, quality of order, delivery price, quality of delivery, customer service, customer satisfaction, and intention to repurchase. The accumulated variate of the measured independent variables is 70.062, with 70.062% explanatory power. The results of a rotated factor analysis are presented in
Table 5. Each factor is represented, in order, as QOI, QOO, POD, QOD, CSV, CSF, and IFR in the table.
4.2.3. Correlation Analysis
Correlation refers to the relationship between each variable. It refers to how the change in one variable leads to a change in the strength and/or direction of another variable. The closer the absolute value is to one, the higher the correlation is. Thus, “+” indicates a positive direction of change, whereas “–” indicates a negative direction.
As presented in
Table 6, the correlation coefficients above 0.5 are as follows: quality of information-quality of order, quality of information-quality of delivery, quality of order-quality of delivery, quality of information-price of delivery, quality of order-price of delivery, quality of delivery-price of delivery, quality of order-customer service, quality of delivery-customer service, quality of price-customer service, quality of information-customer satisfaction, quality of delivery-customer satisfaction, and customer satisfaction-degree of repurchase. The other correlation coefficients between variables are below 0.5, indicating low correlations. As correlation coefficients do not usually exceed 0.5, it can be concluded that there are no multicollinearity problems.
4.3. Hypothesis Testing and Interpretation
To examine the effects of logistics service quality on customer satisfaction in the Chinese online shopping industry, this study conducted regression analyses by establishing five sub-factors as independent variables, with customer satisfaction as the dependent variable.
The results of testing the research hypotheses are as follows:
First, Hypothesis 1predicts that the quality of information positively influences online shopper satisfaction. The regression analysis of Hypothesis 1 gives a P value of 0.020 (<0.05), indicating a statistically significant correlation. Thus, Hypothesis 1 is accepted.
Hypothesis 2 predicts that the quality of order positively influences online shopper satisfaction. The regression analysis of Hypothesis 2 has P = 0.000 < 0.05, indicating a statistically significant correlation. Thus, Hypothesis 2 is accepted.
Hypothesis 3 predicts that the quality of delivery positively influences online shopper satisfaction. The regression analysis of Hypothesis 3 has P = 0.002 < 0.05, indicating a statistically significant correlation. Thus, Hypothesis 3 is accepted.
Hypothesis 4 predicts that a delivery fee positively influences online shopper satisfaction. The regression analysis of Hypothesis 4 has P = 0.042 < 0.05, indicating a statistically significant correlation. Thus, Hypothesis 4 is accepted.
Hypothesis 5 predicts that customer service positively influences online shopper satisfaction. The regression analysis of Hypothesis 5 has P = 0.000 < 0.05, indicating a statistically significant correlation. Thus, Hypothesis 5 is accepted.
Hypothesis 6 predicts that customer satisfaction positively influences customers’ intention to repeat their purchase online. The regression analysis of Hypothesis 6 has F = 81.415, P = 0.000 < 0.05, indicating a statistically significant correlation. Thus, Hypothesis 6 is accepted.
These results indicate that as customers feel increasingly satisfied by online shopping, they tend to show more loyalty towards online shopping malls by repurchasing from the same mall or recommending it to other people.
A summary of the hypotheses tests is presented in
Table 7.
For the online shopping industry to secure a comparative advantage in China, good quality of information, quality of order, quality of delivery, friendly customer service, and adequate delivery charges were found to be the important factors that determine logistics service quality.
The experiment proves the importance of considering the standardized coefficients of quality of delivery (β = 0.328, t = 3.155) and quality of information (β = 0.263, t = 2.375) as higher than those of the other factors in logistics service quality. It proves that customer satisfaction rates have a stronger influence than any other factor influencing the logistics service quality of the online shopping industry. Furthermore, this study found that the quality of order (β = 0.076, t = 3.633) and customer service (β = 0.015, t = 3.801) exert influence. However, their influences are not as strong as those of the previous two factors. Thus, online shopping malls must realize the significance of improving the accuracy and quality of delivery.
The online shopping industry in China is affected by issues regarding delivery punctuality and damages incurred to products during the delivery process. Although many delivery companies are attempting to solve these problems, improvements are yet to be made. Thus, to successfully manage the logistics service quality, online shopping malls in China should focus on enabling fast, accurate, and safe logistics services.
5. Conclusions
5.1. Research Summary and Conclusion
This study found that the quality of an online shopping logistics service influences customer satisfaction, which drives repeat purchasing behavior. Five hypotheses were established to represent the relationship between customer satisfaction and each factor of the logistics service; namely, quality of information, quality of order, quality of delivery, price of delivery, customer service, and customer satisfaction. Each subject from a sample of 150 Chinese customers with online shopping experience was sent a questionnaire. The results of the empirical analysis show that the quality of a logistics service has a statistically significant impact on customer satisfaction and that quality of delivery is the main factor of influence. Furthermore, the results show that customer satisfaction has a statistically significant impact on repeat purchasing behavior. The results provide insights into the strategy behind China’s fast-growing online shopping industry, which focuses on maintaining stability through long-term customer relationship management. The factors affecting customer satisfaction in the online shopping industry are quality of order, quality of information, quality of delivery, price of delivery, and customer service. Furthermore, customer satisfaction affects the intention to repurchase. In conclusion, strategic management of the factors that affect customer satisfaction can increase customers’ intentions to repurchase.
5.2. Research Implications and Future Research Directions
The results of this research provide various theoretical meanings for online shopping logistics services, which can be considered for empirical analysis. This, in turn, can be used to suggest several policies and solutions to assist online shopping malls in establishing customer-oriented strategies that improve quality management. This study suggests practical semantics to direct the operations and management of online shopping transactions and to effectively pursue customer-oriented strategies.
The implications of this study and future directions for research are as follows. First, the scale of online shopping in China is increasing gradually. Accordingly, the number of Internet users is increasing. China joined the World Trade Organization and signed a free-trade agreement with Korea in early 2016, and, thus, the documented information related to the Chinese online shopping industry is important for businesses attempting to enter the market.
Second, the literature on the logistics services of online shopping is insufficient, therefore warranting further research on leading variables. These determinants of logistics service quality were found to yield similar results to the factors related to online shopping mall success as well as the factors previously related to service quality. However, some limitations to these determinants remain. In the future, various determinant factors should be systematically researched and analyzed, enabling the extraction of factors constituting logistics service quality.
Third, online shopping logistics service is an important factor in competition between online shopping malls. Considering that the cost of return shipping is problematic, it is essential that this topic be studied further.
To extract and measure the determining factors of logistics service quality in online shopping, a method of measurement that eliminates subjectivity must be developed. An improved measurement index for customer satisfaction should also be created.
Fourth, the prediction by the 2017 information and technology (IT) market is that service platforms will continuously evolve in line with the mobile era. As the Chinese market transforms, many mobile-based online-to-offline (O2O) services are attracting large-scale investment and experiencing rapid growth.
O2O, a buzzword of the 2017 IT market, is a service devised to organically converge online and offline markets. Based on ICT, O2O attracts customers online and then provides them with services offline. In other words, customers purchase products and services online, and the actual services are provided offline. This is also referred to as a bilateral marketing technique.
Many countries around the world, including China and Korea, are utilizing O2O services that serve as the bridge between online payment and offline service. Examples include placing an order for food delivery, reserving a taxi, and searching for lodgings through a mobile application. As O2O services grow in diversity, so will their customer base. Future studies should develop indices and conduct research in this area.
Lastly, due to the small sample size in the empirical analysis, a structural equation model could not be used. This model may be employed as an alternative estimation approach with a large sample in the future.