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Customer experience: a systematic literature review and consumer culture theory-based conceptualisation

• Published: 15 February 2020
• Volume 71 , pages 135–176, ( 2021 )

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• Muhammad Waqas 1 ,
• Zalfa Laili Binti Hamzah 1 &
• Noor Akma Mohd Salleh 2  

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The study aims to summarise and classify the existing research and to better understand the past, present, and the future state of the theory of customer experience. The main objectives of this study are to categorise and summarise the customer experience research, identify the extant theoretical perspectives that are used to conceptualise the customer experience, present a new conceptualisation and conceptual model of customer experience based on consumer culture theory and to highlight the emerging trends and gaps in the literature of customer experience. To achieve the stated objectives, an extensive literature review of existing customer experience research was carried out covering 49 journals. A total of 99 empirical and conceptual articles on customer experience from the year 1998 to 2019 was analysed based on different criteria. The findings of this study contribute to the knowledge by highlighting the role of customer attribution of meanings in defining their experiences and how such experiences can predict consumer behaviour.

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We would like to thank editor-in-chief (Prof. Dr Joern Block), and the anonymous reviewers for their constructive comments on this paper.

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Waqas, M., Hamzah, Z.L.B. & Salleh, N.A.M. Customer experience: a systematic literature review and consumer culture theory-based conceptualisation. Manag Rev Q 71 , 135–176 (2021). https://doi.org/10.1007/s11301-020-00182-w

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Received : 08 May 2019

Accepted : 10 February 2020

Published : 15 February 2020

Issue Date : February 2021

DOI : https://doi.org/10.1007/s11301-020-00182-w

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ORIGINAL RESEARCH article

Impact of pricing and product information on consumer buying behavior with customer satisfaction in a mediating role.

• 1 Department of Product Design, School of Fine Arts, Guizhou Minzu University, Guiyang, China
• 2 School of Mechanical Engineering, Guizhou University, Guiyang, China
• 3 School of Data Science and Information Engineering, Guizhou Minzu University, Guiyang, China
• 4 School of Mechanical Engineering, Guiyang University, Guiyang, China

The relationship between product pricing and product packaging plays an important role in the buying behavior of consumers, whereas customer satisfaction plays a mediating role. To test these hypotheses, research was conducted on university students in China. Questionnaire-based convenience sampling was conducted on 500 students for data collection using online and offline sources. A total of 367 (73%) students responded, and 17 questionnaires were rejected due to missing information. SPSS and AMOS software were used for the data analysis. Product pricing and product information were independent variables in this study, whereas consumer buying behavior was a dependent variable. Customer satisfaction is mediated by one dependent and two independent variables. Confirmatory factor analysis, path analysis, and discriminant validity in structural equation modeling revealed that product pricing and packaging had a statistically significant relationship with the buyer decision process. The introduction of satisfaction as a mediating variable led to the observation of full mediation in the case of product pricing and partial mediation in product packaging. Given the results of this research, product managers should adopt pricing tactics along with product packaging to influence the buying intentions of consumers.

Introduction

In the competitive market of commodities, products, varieties, consumers, ethnicities, and preferences, product pricing and product packaging information descriptions have a considerable influence on the buying behavior of consumers. To explore the cumulative effects of product pricing and packaging on the buying behavior of consumers of different ethnicities, it is essential to research these aspects of marketing. It is worth mentioning that consumer satisfaction also plays a decisive and mediating role in the development and molding of buying behavior of consumers ( Larsen et al., 2017 ). It is believed that pricing has a significant effect on the buying behavior of consumers because the higher a product is priced, the fewer units are sold. By contrast, products selling at prices lower than the market rate are assumed to sell at a higher volume ( Sadiq M. W. et al., 2020 ). Several studies have shown that pricing is more critical and relevant to consumer buying behavior ( Huo et al., 2021 ).

When discussing the combined effect of product pricing and packaging relationships on consumer buying behavior, pricing alone plays a more critical role than packaging, which has a partial role in buying behavior ( Jabarzare and Rasti-Barzoki, 2020 ). Thus, using this analogy, products can be sold, surprisingly, at a much higher volume. One can increase the prices of the products if the competitor products are scarce in the market or if the manufacturers are low in number. This behavior may not affect the number of sales or the attitude of the consumer toward buying. If the product is already in abundance in the market, then pricing will definitely play an important role because the increase in price will discourage customers from buying it. Similarly, if prices are lowered under such market conditions, then consumers will increase the amount that they purchase significantly.

Even though product pricing has a greater influence than product packaging on the decision process of a buyer ( Pratama and Suprapto, 2017 ; Abdullah et al., 2021 ), high prices in a highly competitive market can lose customers permanently due to the effect of increased pricing ( Kotler et al., 2012 ). While talking about the packaging of products, it should be kept in mind that packaging has a significant relationship on consumers and their decision making about product purchases ( Sadiq M. W. et al., 2020 ). For example, quality, color, and material can have a positive effect on consumers ( Rambabu and Porika, 2020 ). Most consumers desire a range of product choices when purchasing, in terms of packaging. Thus, marketers should place a premium on creative and exclusive packaging that is distinctive in scale, instruction, convenience, product design, and form when compared with rivals in the market segment ( Li et al., 2021 ). Marking a product with accurate information adds to its value. Consumers are attracted to detailed labels, content, and packaging. Many people are influenced by the way a product is packaged and presented in the market. While the product itself may be of any quality, the relationship it produces through its packaging has a strong influence on the purchasing attitude of the consumer. Nowadays, eco-friendly packaging is essential. Thus, advertisers should prioritize this factor and employ best practices to the maximum degree possible, including eco-friendly recyclable packaging ( Abdullah et al., 2021 ). Consumer buying behavior also has a lot to do with product selling and buying ( Brun et al., 2014 ), although some customers are not influenced by the packaging or labeling of products, buying is demand-driven or need-oriented by most consumers.

However, super packaging or labeling of products may not attract the consumer for several reasons. One of the primary reasons may be the high price and packaging, announcing the excellent quality of the product. In such cases, there may be a lack of interest by the consumer toward attractive packaging; instead, they may prefer to buy local products that are cheap and readily available in the market. According to Tu and Chih (2013) , consumer satisfaction is another aspect of product selling and consumer buying behavior. It also plays a mediating role in product buying behavior, pricing, and packaging ( Rambabu and Porika, 2020 ). Even though a price might be negotiable and the product is provided with helpful information and good, decent packaging, there is a lot to do to satisfy a consumer. All of these factors are correlated with consumer satisfaction. If the consumer is satisfied with all these, they may buy the product, but there is no guarantee of this. Thus, consumer buying behavior is also influenced by satisfaction ( Brun et al., 2014 ). This study seeks to answer several questions to explain consumer buying behavior in relation to product pricing and packaging, with consumer satisfaction as a mediating factor. In this work, we first present a brief review of this research, which differs from the current literature in various respects. The research has generated several findings.

• Product prices significantly correlate with consumer buying behavior.

• The product information available on packaging influences the consumer’s buying behavior.

• Satisfaction plays a mediating role in consumer buying behavior.

• Pricing of the product plays an essential role in customer satisfaction.

• Product information available on labels plays a significant role in customer satisfaction.

The remainder of this work is structured as follows: Section “Review of Literature and Hypothesis Development” presents a review of previous studies supporting different theoretical frameworks. Section “Research Methodology” presents the methodology adopted for the empirical analysis. Section “Data Analysis and Results” presents the results of this analysis. Section “Conclusion and Recommendations” concludes the present study, limitations and future directions.

Review of Literature and Hypothesis Development

Product pricing and consumer buying behavior.

Product pricing seems to be the only direct element that generates revenue and indicates the success or failure of a product or service. As a result, the researchers in this study chose to emphasize this aspect. Manali (2015) carried out research into the theoretical dimensions of consumer purchasing behavior and the factors that affect it. He analyzed the relationship between consumer buying behavior and factors affecting the buying process and decisions of the consumers. His research provides enough evidence to show that the internal and external influences of a consumer have a major relationship with their purchasing behavior.

According to Al-Salamin et al. (2015) , good prices of well-known brands negatively affect the purchasing process. Young people are eager to buy brands, but their low income hinders them from doing so. The only aspect of the marketing mix that generates revenue is price, whereas the others generate costs. The authors also noted that the purchasing decisions of consumers focus on their price perception and what they think about the actual price of a product. The main goal of marketing is to understand how customers move toward their price perception. We are all customers, no matter how old, educated, wealthy, or talented. Understanding customer behavior thus becomes a critical challenge for advertisers, distributors, and salespeople. Therefore, we hypothesized the following:

H 1 : Product pricing is significantly correlated with consumer buying behavior.

Product Packaging and Consumer Buying Behavior

Packaging a product with relevant product details contributes positively to consumer buying behavior. Names, features, and product packaging attract consumers. Many people are influenced by the packaging and marketing of items. While a product may be of any quality, the impact on customer purchasing is essential ( Rundh, 2009 ; Li et al., 2021 ; Naseem et al., 2021 ). The aim of this study was to determine the effect of product pricing and information about product packaging on the buying behavior of consumers. Innovation in product labeling and packing often has a major relationship with demand, which is why there are many methods for this type of action plan if a company wants to pursue this strategy with regard to its product packaging. When it comes to packaging, many buyers want a range of product choices. Therefore, marketers should pay high prices for innovative and exclusive packaging that differentiate their products from the competition in terms of size, guidance, functionality, product innovation, and shape ( Rundh, 2009 ; Li et al., 2021 ; Sarfraz et al., 2021 ). For the target consumer, product packaging acts as an outstanding networking tool, ultimately increasing their awareness levels. Packaging must highlight key aspects of the product and brand, such as material composition, purpose, and quality. To show respect for customers, packaging should include all of this information in regional languages. Not only is efficient packaging important for storing and preserving products, but it is also important for creating an interest in and generating actions toward purchasing the product. Packaging that is environmentally friendly has become increasingly important. As a result, marketers should place a high priority on this aspect and use best practices to the greatest possible extent, including the use of environmentally friendly recycled materials ( Deliza and MacFie, 2001 ; Abdullah et al., 2021 ; Mohsin et al., 2021 ).

H 2 : Product information on packaging is significantly related to consumer purchasing behavior.

Satisfaction of Consumers and Their Buying Behavior

Customer value and customer satisfaction are considered important parameters for the relationship between customer value and the willingness to sacrifice ( Zechmeister et al., 1997 ). This sacrifice is made in accordance with an exchange mechanism that includes transaction costs and the risk of the goods of the company. According to Larsen et al. (2017) , customers will be disappointed in the future if the ratio value considered by the economic sacrifice of customers with the goods sold by the company does not meet their expectations. Customers will be satisfied if the ratio value is sufficient or exceeds their expectations. Another analysis of consumer value examines the understanding of customers of the quality and benefits of toothpaste in relation to price sacrifice. Social, emotional, and functional values are all aspects of customer value ( Keller and Kotler, 2012 ).

Customer satisfaction is evaluated by obtaining feedback from customers after purchasing products or services, and then comparing it with their expectations. Customer satisfaction is calculated using the performance requirements of products or services that are capable of satisfying the needs and desires of customers. A satisfied consumer is a consumer who believes that the products or services were worth purchasing, which would encourage them to buy the products again. On the other hand, a frustrated consumer will persuade other consumers not to buy the same brand, which ultimately causes switching to rival brands. According to Tu and Chih (2013) , “customer satisfaction is perceived as affecting repurchasing intentions and actions, which, in turn, contributes to an organization’s potential sales and income.”

H 3 : Satisfaction plays a mediating role in consumer buying behavior.

Role of Product Pricing on Consumer Satisfaction

Price is regarded as something that can be calculated according to several measures, such as a reasonable price, a competitive price, a discounted price, a retailer’s price, and price suitability. Value is a higher-level definition than quality and price because it is more individualistic and personal. A satisfied consumer believes that the value of goods and services is comparable with the price, which will encourage them to repurchase the products. According to Zeithaml (1988) , “quality can be characterized as superiority or excellence in a broad sense.” From the customer’s perspective, “The price is given up or sacrificed to get the product or service” ( Zeithaml, 1988 ). According to Bei and Chiao (2001) , “[P]rice is described as giving or sacrificing for the acquisition of a service or product,” while Kotler et al. (2012) proposed that “the price is the amount paid for a product or service and the sum of the value exchanged by consumers for the advantages of a product or service available or being used.” The perceptions of customers of a given price can have a direct relationship with the their decision to buy a product ( Zechmeister et al., 1997 ). Customers will pay attention to the prices paid by their peers, and no one wants to spend more money than their peers do. The fairness of a price can affect the perception of consumers of the product, and ultimately their desire to become a consumer.

H 4 : The pricing of a product plays a significant role in customer satisfaction.

Role of Product Packaging on Consumer Satisfaction

Packaging and labeling can be considered one of the most important tools in marketing and communication, which means that a thorough examination of their components and their relationships with consumer buying behavior is necessary. According to Joewono and Kubota (2007) , consumer satisfaction results from product and service reviews based on customer perceptions and a broad assessment of the overall consumption experience. It is suggested that customer satisfaction affects repurchase intentions and actions, which, in turn, determine potential sales and revenue for a company. According to Zeithaml (2000) , consumer satisfaction is measured on a multidimensional scale that includes service quality, product quality, scenario factors, personal factors, and price factors.

Product packaging plays a variety of roles. It provides information about the product and the company, connects them with customers, and ensures product quality ( Naseem et al., 2020 ; Rambabu and Porika, 2020 ). It is important to remember that packaging has a significant influence on customers and their purchasing decisions. Consumers react positively to quality, color, and content. Similarly, if a product is labeled with accurate information about the product, it increases the value of the product. Consumers respond to a product’s specific name, ingredients, and packaging. Many consumers are concerned about the way a product is designed and advertised. Although the quality of the product itself may vary, the effect of packaging on customer purchasing decisions is important.

H 5 : Product information available on labels plays a significant role toward customer satisfaction.

Theoretical Support of the Study

The following research was conducted to investigate underlying issues. This study is a continuation of expectancy disconfirmation theory (EDT) and social cognitive theory (SCT). Both theories provide a strong background for conducting this research. According to EDT, the satisfaction of consumers is linked to the expectation and perception of product quality. A consumer sets an expectation before examining a product in real time. This comparison of preset expectations with real-sense performance is the basis of EDT. In this study, consumer satisfaction plays a mediating role between product pricing, product packaging, and consumer buying behavior. The expectations of consumers are based on the price of the product, information on product packaging, and perceived quality.

The other central backbone of this research is SCT, developed by Bandura (2012) , which explains that learning takes place in a social context with a complex and reciprocal relationship between the individual, their environment, and their actions. The emphasis on social relationships, and also external and internal social reinforcement, is a distinctive feature of SCT. SCT considers the specific ways in which people maintain their behavior and interact with others. It also considers the specific ways in which people learn and sustain behaviors and the social context in which they do so. According to this theory, past experiences strengthen ideas and expectations, all of which affect whether a person maintains his/her attitudes. Many behavioral models that are used in studies related to health do not include behavior maintenance; instead, they focus on behavior initiation. This is a shame because the real purpose of public health is to maintain conduct rather than initiate it. SCT aims to illustrate how people monitor and reinforce their actions to achieve goal-directed behavior that can be managed. Thus, the product pricing and packaging of a product with useful information on labels will surely correlate with consumer buying behavior that will persist. The customer will buy or not buy in the future on the basis of the expectations and perceptions of the product once his behavior about the product has already been initiated. A conceptual framework was developed to focus on the specific variables. The framework consists of the hypotheses shown in Figure 1 .

Figure 1. Theoretical framework.

Research Methodology

The research methodology of a study represents an essential and integral part of the entire process and explains how science contributes to aims. The behavioral approach of respondents, i.e., expectations, evidence, observations, knowledge of reality, and individual point of view, can be summarized by analytical parameters. According to James and Vinnicombe (2002) , the assurance of objectivity in the scientific procession is compulsory. Furthermore, a perspective emphasizing social variable is considered essential by the society for practical implications ( Blaikie, 2007 ). Their innovative discoveries and interpretation are leading activities of label research.

Research Design

In this research, the structure of behavior science by Zechmeister et al. (1997) is followed with mediation and description for the problem-solving process. The main focus of this research is the state of mind, mood swings, variations in feelings, and behavior toward the specific situation of the respondents. In addition, the organizational performance in the market and consumer buying behavior can solve many problems by approaching the cooperative feedback process with peers and accumulating knowledge. The analysis of buying behavior may be categorized as “co-oriented” or “comparative.” According to behavioral science, these two factors have real meaning. This study seeks to understand the effect of product pricing and packaging on the buying behavior of consumers. At the same time, satisfaction plays its role as a mediating variable ( Zechmeister et al., 1997 ; Bollen and Pearl, 2013 ). For data collection, self-administered questionnaires were used for quantitative analysis.

Study Population

The sample of this study comprises students from different universities in China. The main reason for choosing university students is that recent research concentrates on product pricing with consumer buying behavior while considering university students as their population. The population selection is based on the area of interest and importance, which covers the objectivity of this research. Divergent online and offline sources were used to collect analytical data. The questionnaires were circulated among 500 students, and the 367 replied to us regarding that, and so the aggregate received response was 73%. Seventeen answers received from respondents were rejected due to incomplete information, and 350 were finalized for the analytical process. This study used convenience sampling for data collection. Bonds-Raacke and Raacke (2012) suggested that field examinations should use a questionnaire. The researcher used a questionnaire to collect the data in this study. SPSS software was used to check the quality, validity, and scale reliability of the instrument.

Data Analysis and Results

SPSS and AMOS software were used for the data analysis. Table 1 presents the reliability analysis results. Product pricing and product information are independent variables in this study, whereas consumer buying behavior is a dependent variable. In this study, satisfaction is mediated between two independent variables and one dependent variable. All variables have acceptable reliability alpha values.

Table 1. Reliability analysis.

Table 2 shows the descriptive statistics. The mean value of product pricing is 3.4, where product information has a mean value of 3.9, satisfaction has a mean value 3.6, and consumer buying behavior has a mean value of 3.8.

Table 2. Descriptive statistics.

The product price measuring scale was introduced by Lichtenstein et al. (1993) . The Likert scale ranges from strongly agree to strongly disagree, and this scale was used in this research with slight modifications. The Lichtenstein et al. (1993) ranking was further verified by confirmatory factor analysis (CFA) analysis to meet the requirements of this research. The measuring scales of Brun et al. (2014) and Zekiri and Hasani (2015) were used to measure the product packaging and customer satisfaction. The behavior of consumers toward buying decisions, the measurement scale of Bagga and Bhatt (2013) is used with slight modification to fit the scale for scope and broaden the view of this research. All predefined models/scales were rated on 5-point Likert scale, with higher numerical values indicating greater satisfaction.

Confirmatory Factor Analysis

The pooled CFA is more reliable than other versions and the most up-to-date approach. The AMOS 24 is used to check the relationship among variables ( Afthanorhan et al., 2014 ; Chong et al., 2014 ).

The results of Table 3 declare the structural fitness of the model by meeting all criterion requirements. The reliability values or factor loading of individual items are presented in Figure 2 . The findings of Table 4 have also covered the composite reliability of a wide scale. The composite reliability is indicated by the reliability of the measurement scales while reporting reliability ( Netemeyer et al., 2003 ).

Table 3. Pooled CFA model fitness tests.

Figure 2. Pooled confirmatory factor analysis.

Table 4. Factor loading of items.

Assessment of Discriminant Validity

Discriminant validity was measured using HTMT analysis by considering two determinants, i.e., supposed to be related or unrelated. The value of cut-off criteria for strict discriminant validity was 0.850, and for liberal discriminant validity it was 0.900 ( Henseler et al., 2015 ), obtained by employing discriminant validity. The following discriminant validity criteria have provided the results of Table 5 .

Table 5. HTMT analysis.

Path Analysis in Structural Equation Modeling

In this study, structural equation modeling was used to determine the proposed relationships. Exogenous variables were included in this analysis to allow for the study of endogenous variables using AMOS 24. Here, we can see whether the independent and dependent variables are linearly related to each other. The analytical observations and their mean values are tabulated and linked with the collected information. The results of Table 6 declare the structural fitness of the model by meeting all criterion requirements.

Table 6. SEM, model fitness tests.

Figure 3 shows the direct effects of the independent variables on the dependent variable. In this figure, the mediator variable is missing from this path analysis diagram to capture the direct correlation of the independent variable on the dependent variable.

Figure 3. Direct effects of path analysis.

Table 7 shows that H 1 , H 3 , and H 5 are statistically significant, and their P-value is less than 0.05, which shows the 95% confidence interval. The structural equation modeling with the path analysis is presented in Figure 4 . The path analysis declared the nature of variables, i.e., two variables are independent: one is the mediator and the other one is dependent.

Table 7. Results of indirect effects.

Figure 4. Indirect direct effects of path analysis.

The findings of Table 8 indicate that both hypotheses are statistically significant, but the observed mediation values for these hypotheses differ. H 2 is statistically significant but has a full mediation effect, whereas H 4 is statistically significant and has a partial mediation effect.

Table 8. Results of indirect effects.

Hypothetical Results

The results of the hypothesis are shown in Table 9 in a more detailed and comprehensive manner. To calculate the standard error with T and P-values and the significance of the path coefficient, bootstrapping (1,000 subsamples) was used, which provided direct evidence of the hypotheses being accepted or rejected. The structural model analysis results show the path coefficients and their significance levels, as presented in Table 9 . The findings confirmed that all five relationships were significant, and it can be concluded that H 1 , H 2 , H 3 , H 4 , and H 5 were supported.

Table 9. Hypothesis results.

According to Sisodiya and Sharma (2018) , the marketing mix has a significant influence on the buying behavior of consumers. In this study, the main principle in packaging is to “reach a greater height of opportunity.” It is often regarded as a critical component of purchase decision making, and has often been shown to be a way of building market awareness and connecting with consumers outside the product itself and across several channels ( Rambabu and Porika, 2020 ; Sadiq W. et al., 2020 ). Packaging performs multidimensional functions. It can not only offer knowledge about products and business entities, but it is also a technique for communicating with consumers and safeguarding product quality ( Silayoi and Speece, 2007 ). Pricing can be considered one of the most vital and essential elements that can influence consumer buying behavior or the buyer decision process ( Dhurup et al., 2014 ; Sadiq W. et al., 2020 ).

According to Kotler et al. (2012) , customer satisfaction “is the extent to which a product’s perceived performance matches the buyer’s expectations.” Aslam et al. (2018) stated that price has a positive and significant correlation with customer satisfaction. Furthermore, they believed that the success of the sector was based on price fairness and customer satisfaction. Previous studies have also discussed this phenomenon in connection with other geographical locations. The price factor is more relatable to consumer buying behavior than product packaging ( Jabarzare and Rasti-Barzoki, 2020 ; Huo et al., 2021 ). Product pricing has a greater influence than product packaging on the buyers’ decision processes ( Pratama and Suprapto, 2017 ; Abdullah et al., 2021 ). Innovation in product packaging also has a significant relationship with the consumer; however, if any organization wants to follow a strategy that is relevant to its product packaging, then there are several strategies for this kind of plan of action. Most consumers desire a range of product choices when purchasing, in terms of packaging. Thus, the marketer should place a premium on creative and exclusive packaging that is distinctive in terms of scale, instruction, convenience, product design, and form when compared to rivals in market segmentation ( Rundh, 2009 ; Bollen and Pearl, 2013 ). Product packaging serves as an excellent networking medium for target customers, eventually increasing their knowledge levels. Packaging must convey pertinent details about the product and brand, including ingredient composition, intent, and consistency. In addition, packaging should provide all of this material in regional languages to demonstrate respect for consumers. Efficient packaging is critical not only for storing and protecting goods but also for generating interest in and action toward buying the commodity. Currently, eco-friendly packaging is essential. Thus, advertisers should prioritize this factor and employ best practices to the maximum degree possible, including eco-friendly recyclable packaging ( Deliza and MacFie, 2001 ; Abdullah et al., 2021 ).

Conclusion and Recommendations

The study results clearly show that both product pricing and packaging have a statistically significant relationship with the buyer’s decision process. At the same time, the introduction of satisfaction leads to the observation of full mediation in the case of product pricing and partial mediation in product packaging. Despite knowing that both the variables have a statistically significant relationship with the consumer buying behavior, it is essential to understand the managerial implications. Suppose, we would like to report and recommend these findings to different organizations looking to cut their operational costs in any possible way without compromising product quality, we suggest in such cases that they focus on pricing strategies for a better consumer response. A focus on the product packaging design process, packaging material, or the information available on product packaging positively influences consumer buying behavior. However, its effect is lower than product pricing. Therefore, it is recommended for managers that if they want to connect with their target customers more efficiently and effectively, they should focus on both product pricing and packaging options. However, if they can afford only one option from the product’s operational cost perspective, they must focus on product pricing strategies.

In future studies, it must be kept in mind that these findings pertain directly to the individuals listed as respondents. To make it more accurate, other demographic, psychographic, and geographic samples should be used. It is likely that when data are thus obtained, the findings will differ. To ensure more lasting and repeatable corporate outcomes, several studies are required to obtain results that are more accurate and reliable.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author Contributions

HZ, XY, and ZL contributed to conception and design of the study. HZ organized the database, performed the statistical analysis, and wrote the first draft of the manuscript. XY, ZL, and QY wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

This work was funded by the National Natural Science Foundation of China (52065010), Open Fund of Key Laboratory of Advanced Manufacturing Technology, Ministry of Education (GZUAMT2021KF[07] and GZUAMT2021KF[08]), Natural Science Research Project supported by the Education Department of Guizhou Province [Grant Nos. (2018)152 and (2017)239], Humanities and Social Science Research Project of Guizhou Provincial Department of Education (Grant No. 2018qn46), and the Guiyang University Teaching Research Project (Grant No. JT2019520206).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbreviations

CFA, Confirmatory Factor Analysis; RMSEA, Root Mean Square of Error Approximation; CFI, Comparative fit index; EDT, Expectancy Disconfirmation Theory; SCT, Social Cognitive Theory.

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Keywords : product pricing, product packaging, consumer buying behavior, consumer satisfaction, confirmatory factor analysis, structural equation modeling

Citation: Zhao H, Yao X, Liu Z and Yang Q (2021) Impact of Pricing and Product Information on Consumer Buying Behavior With Customer Satisfaction in a Mediating Role. Front. Psychol. 12:720151. doi: 10.3389/fpsyg.2021.720151

Received: 03 June 2021; Accepted: 08 October 2021; Published: 13 December 2021.

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Copyright © 2021 Zhao, Yao, Liu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Huiliang Zhao, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Open access
• Published: 15 September 2016

An empirical research on customer satisfaction study: a consideration of different levels of performance

• Yu-Cheng Lee 1 ,
• Yu-Che Wang 2 ,
• Shu-Chiung Lu 3 , 4 ,
• Yi-Fang Hsieh 6 ,
• Chih-Hung Chien 3 , 5 ,
• Sang-Bing Tsai 7 , 8 , 9 , 10 , 11 , 12 &
• Weiwei Dong 13  

SpringerPlus volume  5 , Article number:  1577 ( 2016 ) Cite this article

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Customer satisfaction is the key factor for successful and depends highly on the behaviors of frontline service providers. Customers should be managed as assets, and that customers vary in their needs, preferences, and buying behavior. This study applied the Taiwan Customer Satisfaction Index model to a tourism factory to analyze customer satisfaction and loyalty. We surveyed 242 customers served by one tourism factory organizations in Taiwan. A partial least squares was performed to analyze and test the theoretical model. The results show that perceived quality had the greatest influence on the customer satisfaction for satisfied and dissatisfied customers. In addition, in terms of customer loyalty, the customer satisfaction is more important than image for satisfied and dissatisfied customers. The contribution of this paper is to propose two satisfaction levels of CSI models for analyzing customer satisfaction and loyalty, thereby helping tourism factory managers improve customer satisfaction effectively. Compared with traditional techniques, we believe that our method is more appropriate for making decisions about allocating resources and for assisting managers in establishing appropriate priorities in customer satisfaction management.

Traditional manufacturing factories converted for tourism purposes, have become a popular leisure industry in Taiwan. The tourism factories has experienced significant growth in recent years, and more and more tourism factories emphasized service quality improvement, and customized service that contributes to a tourism factory’s image and competitiveness in Taiwan (Wu and Zheng 2014 ). Therefore, tourism factories has become of greater economic importance in Taiwan. By becoming a tourism factory, companies can establish a connection between consumers and the brand, generate additional income from entrance tickets and on-site sales, and eventually add value to service innovations (Tsai et al. 2012 ). Because of these incentives, the Taiwanese tourism factory industry has become highly competitive. Customer satisfaction is seen as very important in this case.

Numerous empirical studies have indicated that service quality and customer satisfaction lead to the profitability of a firm (Anderson et al. 1994 ; Eklof et al. 1999 ; Ittner and Larcker 1996 ; Fornell 1992 ; Anderson and Sullivan 1993 ; Zeithaml 2000 ). Anderson and Sullivan ( 1993 ) stated that a firm’s future profitability depends on satisfying current customers. Anderson et al. ( 1994 ) found a significant relationship between customer satisfaction and return on assets. High quality leads to high levels of customer retention, increase loyalty, and positive word of mouth, which in turn are strongly related to profitability (Reichheld and Sasser 1990 ). In a tourism factory setting, customer satisfaction is the key factor for successful and depends highly on the behaviors of frontline service providers. Kutner and Cripps ( 1997 ) indicated that customers should be managed as assets, and that customers vary in their needs, preferences, buying behavior, and price sensitivity. A tourism factory remains competitive by increasing its service quality relative to that of competitors. Delivering superior customer value and satisfaction is crucial to firm competitiveness (Kotler and Armstrong 1997 ; Weitz and Jap 1995 ; Deng et al. 2013 ). It is crucial to know what customers value most and helps firms allocating resource utilization for continuously improvement based on their needs and wants. The findings of Customer Satisfaction Index (CSI) studies can serve as predictors of a company’s profitability and market value (Anderson et al. 1994 ; Eklof et al. 1999 ; Chiu et al. 2011 ). Such findings provide useful information regarding customer behavior based on a uniform method of customer satisfaction, and offer a unique opportunity to test hypotheses (Anderson et al. 1997 ).

The basic structure of the CSI model has been developed over a number of years and is based on well-established theories and approaches to consumer behavior, customer satisfaction, and product and service quality in the fields of brands, trade, industry, and business (Fornell 1992 ; Fornell et al. 1996 ). In addition, the CSI model leads to superior reliability and validity for interpreting repurchase behavior according to customer satisfaction changes (Fornell 1992 ). These CSIs are fundamentally similar in measurement model (i.e. causal model), they have some obvious distinctions in model’s structure and variable’s selection. Take full advantages of other nations’ experiences can establish the Taiwan CSI Model which is suited for Taiwan’s characters. Thus, the ACSI and ECSI have been used as a foundation for developing the Taiwan Customer Satisfaction Index (TCSI). The TCSI was developed by Chung Hua University and the Chinese Society for Quality in Taiwan. The TCSI provides Taiwan with a fair and objective index for producing vital information that can help the country, industries, and companies improve competitiveness. Every aspect of the TCSI that influences overall customer satisfaction can be measured through surveys, and every construct has a cause–effect relationship with the other five constructs (Fig.  1 ). The relationships among the different aspects of the TCSI are different from those of the ACSI, but are the same as those of the ECSI (Lee et al. 2005 , 2006 ).

The Taiwan Customer Satisfaction Index model

The traditional CSI model for measuring customer satisfaction and loyalty is restricted and does not consider the performance of firms. Moreover, as theoretical and empirical research has shown, the relationship between attribute-level performance and overall satisfaction is asymmetric. If the asymmetries are not considered, the impact of the different attributes on overall satisfaction is not correctly evaluated (Anderson and Mittal 2000 ; Matzler and Sauerwein 2002 ; Mittal et al. 1998 ; Matzler et al. 2003 , 2004 ). Few studies have investigated CSI models that contain different levels of performance (satisfaction), especially in relation to satisfaction levels of a tourism factory. To evaluate overall satisfaction accurately, the impact of the different levels of performance should be considered (Matzler et al. 2004 ). The purpose of this study is to apply the TCSI model that contains different levels of performance to improve and ensure the understanding of firm operational efficiency by managers in the tourism factory. A partial least squares (PLS) was performed to test the theoretical model due to having been successfully applied to customer satisfaction analysis. The PLS is well suited for predictive applications (Barclay et al. 1995 ) and using path coefficients that regard the reasons for customer satisfaction or dissatisfaction and providing latent variable scores that could be used to report customer satisfaction scores. Our findings provide support for the application of TCSI model to derive tourist satisfaction information.

Literature review

National customer satisfaction index (csi).

The CSI model includes a structural equation with estimated parameters of hidden categories and category relationships. The CSI can clearly define the relationships between different categories and provide predictions. The basic CSI model is a structural equation model with latent variables which are calculated as weighted averages of their measurement variables, and the PLS estimation method calculates the weights and provide maximum predictive power of the ultimate dependent variable (Kristensen et al. 2001 ). Many scholars have identified the characteristics of the CSI (Karatepe et al. 2005 ; Malhotra et al. 1994 ).

Although the core of the models are in most respects standard, they have some obvious distinctions in model’s structure and variable’s selection so that their results cannot be compared with each other and some variations between the SCSB (Swedish), the ACSI (American), the ECSI (European), the NCSB (Norwegian) and other indices. For example, the image factor is not employed in the ACSI model (Johnson et al. 2001 ); the NCSB eliminated customer expectation and replaced with corporate image; the ECSI model does not include the customer complaint as a consequence of satisfaction. Many scholars have identified the characteristics of the CSI (Karatepe et al. 2005 ; Malhotra et al. 1994 ). The ECSI model distinguishes service quality from product quality (Kristensen et al. 2001 ) and the NCSB model applies SERVQUAL instrument to evaluate service quality (Johnson et al. 2001 ). A quality measure of a single customer satisfaction index is typically developed according to a certain type of culture or the culture of a certain country. When developing a system for measuring or evaluating a certain country or district’s customer satisfaction level, a specialized customer satisfaction index should be developed.

As such, the ACSI and ECSI were used as a foundation to develop the TCSI. The TCSI was developed by Chung Hua University and the Chinese Society for Quality. Every aspect of the TCSI that influences overall customer satisfaction can be measured through surveys, and every construct has a cause–effect relationship with the other five constructs. The TCSI assumes that currently: (1) Taiwan corporations have ability of dealing with customer complaints; customer complaints have already changed from a factor that influences customer satisfaction results to a factor that affects quality perception; (2) The expectations, satisfaction and loyalty of customers are affected by the image of the corporation. The concept that customer complaints are not calculated into the TCSI model is that they were removed based on the ECSI model (Lee et al. 2005 , 2006 , 2014a , b ; Guo and Tsai 2015 ; Tsai et al. 2015a , b ; 2016a ).

TCSI model and service quality

Service quality is frequently used by both researchers and practitioners to evaluate customer satisfaction. It is generally accepted that customer satisfaction depends on the quality of the product or service offered (Anderson and Sullivan 1993 ). Numerous researchers have emphasized the importance of service quality perceptions and their relationship with customer satisfaction by applying the NCSI model (e.g., Ryzin et al. 2004 ; Hsu 2008 ; Yazdanpanah et al. 2013 ; Chiu et al. 2011 ; Temizer and Turkyilmaz 2012 ; Mutua et al. 2012 ; Dutta and Singh 2014 ). Ryzin et al. ( 2004 ) applied the ACSI to U.S. local government services and indicated that the perceived quality of public schools, police, road conditions, and subway service were the most salient drivers of satisfaction, but that the significance of each service varied among income, race, and geography. Hsu ( 2008 ) proposed an index for online customer satisfaction based on the ACSI and found that e-service quality was more determinative than other factors (e.g., trust and perceived value) for customer satisfaction. To deliver superior service quality, an online business must first understand how customers perceive and evaluate its service quality. This study developed a basic model for using the TCSI to analyze Taiwan’s tourism factory services. The theoretical model comprised 14 observation variables and the following six constructs: image, customer expectations, perceived quality, perceived value, customer satisfaction, and loyalty.

Research methods

The measurement scale items for this study were primarily designed using the questionnaire from the TCSI model. In designing the questionnaire, a 10-point Likert scale (with anchors ranging from strongly disagree to strongly agree) was used to reduce the statistical problem of extreme skewness (Fornell et al. 1996 ; Qu et al. 2015 ; Tsai 2016 ; Tsai et al. 2016b ; Zhou et al. 2016 ). A total of 14 items, organized into six constructs, were included in the questionnaire. The primary questionnaire was pretested on 30 customers who had visited a tourism factory. Because the TCSI model is preliminary research in the tourism factory, this study convened a focus group to decide final attributes of model. The focus group was composed of one manager of tourism factory, one professor in Hospitality Management, and two customers with experience of tourism factory.

We used the TCSI model (Fig.  1 ) to structure our research. From this structure and the basic theories of the ACSI and ECSI, we established the following hypotheses:

Image has a strong influence on tourist expectations.

Image has a strong influence on tourist satisfaction.

Image has a strong influence on tourist loyalty.

Tourist expectations have a strong influence on perceived quality.

Tourist expectations have a strong influence on perceived values.

Tourist expectations have a strong influence on tourist satisfaction.

Perceived quality has a strong influence on perceived value.

Perceived quality has a strong influence on tourist satisfaction.

Perceived value has a strong influence on tourist satisfaction.

Customer satisfaction has a strong influence on tourist loyalty.

The content of our surveys were separated into two parts; customer satisfaction and personal information. The definitions and processing of above categories are listed below:

Part 1 of the survey assessed customer satisfaction by measuring customer levels of tourism factory image, expectations, quality perceptions, value perceptions, satisfaction, and loyalty toward their experience, and used these constructs to indirectly survey the customer’s overall evaluation of the services provided by the tourism factory.

Part 2 of the survey collected personal information: gender, age, family situation, education, income, profession, and residence.

The six constructs are defined as follows:

Image reflects the levels of overall impression of the tourism factory as measured by two items: (1) word-of-mouth reputation, (2) responsibility toward concerned parties that the tourist had toward the tourism factory before traveling.

Customer expectations refer to the levels of overall expectations as measured by two items: (1) expectations regarding the service of employees, (2) expectations regarding reliability that the tourist had before the experience at the tourism factory.

Perceived quality was measured using three survey measures: (1) the overall evaluation, (2) perceptions of reliability, (3) perceptions of customization that the tourist had after the experience at the tourism factory.

Perceived value was measured using two items: (1) the cost in terms of money and time (2) a comparison with other tourism factories.

Customer satisfaction represents the levels of overall satisfaction was captured by two items: (1) meeting of expectations, (2) closeness to the ideal tourism factory.

Loyalty was measured using three survey measures: (1) the probabilities of visiting the tourism factory again (2) attending another activity held by the tourism factory, (3) recommending the tourism factory to others.

Data collection and analysis

The survey sites selected for this study was the parking lots of one food tourism factory in Taipei, Taiwan. A domestic group package and individual tourists were a major source of respondents who were willing to participate in the survey and completed the questionnaires themselves based on their perceptions of their factory tour experience. Four research assistants were trained to conduct the survey regarding to questionnaire distribution and sampling.

To minimize prospective biases of visiting patterns, the survey was conducted at different times of day and days of week—Tuesday, Thursday, Saturday for the first week; Monday, Wednesday, Friday and Sunday for the next week. The afternoon time period was used first then the morning time period in the following weeks. The data were collected over 1 month period.

Of 300 tourists invited to complete the questionnaire, 242 effective responses were obtained (usable response rate of 80.6 %). The sample of tourists contained more females (55.7 %) than males (44.35 %). More than half of the respondents had a college degree or higher, 28 % were students, and 36.8 % had an annual household income of US $10,000–$20,000. The majority of the respondents (63.7 %) were aged 20–40 years.

Comparison of the TCSI models for satisfied and dissatisfied customers

Researchers have claimed that satisfaction levels differ according to gender, age, socioeconomic status, and residence (Bryant and Cha 1996 ). Moreover, the needs, preferences, buying behavior, and price sensitivity of customers vary (Kutner and Cripps 1997 ). Previous studies have demonstrated that it is crucial to measure the relative impact of each attribute for high and low performance (satisfaction) (Matzler et al. 2003 , 2004 ). To determine the reasons for differences, a satisfaction scale was used to group the sample into satisfied (8–10) and dissatisfied (1–7) customers.

The research model was tested using SmartPLS 3.0 software, which is suited for highly complex predictive models (Wold 1985 ; Barclay et al. 1995 ). In particular, it has been successfully applied to customer satisfaction analysis. The PLS method is a useful tool for obtaining indicator weights and predicting latent variables and includes estimating path coefficients and R 2 values. The path coefficients indicate the strengths of the relationships between the dependent and independent variables, and the R 2 values represent the amount of variance explained by the independent variables. Using Smart PLS, we determined the path coefficients. Figures  2 and 3 show ten path estimates corresponding to the ten research hypothesis of TCSI model for satisfied and dissatisfied customers. Every path coefficient was obtained by bootstrapping the computation of R 2 and performing a t test for each hypothesis. Fornell et al. ( 1996 ) demonstrated that the ability to explain the influential latent variables in a model is an indicator of model performance, in particular the customer satisfaction and customer loyalty variables. From the results shown, the R 2 values for the customer satisfaction were 0.53 vs. 0.50, respectively; and the R 2 value for customer loyalty were 0.64 vs. 0.60, respectively. Thus, the TCSI model explained 53 vs. 50 % of the variance in customer satisfaction; 64 vs. 60 % of that in customer loyalty as well.

Path estimate of the TCSI model for satisfied customers. *p < 0.05; **p < 0.01; ***p < 0.001

Path estimate of the TCSI model for dissatisfied customers. *p < 0.05; **p < 0.01; ***p < 0.001

According to the path coefficients shown in Figs.  2 and 3 , image positively affected customer expectations (β = 0.58 vs. 0.37), the customer satisfaction (β = 0.16 vs. 0.11), and customer loyalty (β = 0.47 vs. 0.16). Therefore, H1–H3 were accepted. Customer expectations were significantly related to perceived quality (β = 0.94 vs. 0.83). However, customer expectations were not significantly related to perceived value shown as dotted line (β = −0.01 vs. −0.20) or the customer satisfaction, shown as dotted line (β = −0.21 vs. −0.32). Thus, H4 was accepted but H5 and H6 were not accepted. Perceived value positively affected the customer satisfaction (β = 0.27 vs. 0.14), supporting H7. Accordingly, the analysis showed that each of the antecedent constructs had a reasonable power to explain the overall customer satisfaction. Furthermore, perceived quality positively affected the customer satisfaction (β = 0.70 vs. 0.62), as did perceived value (β = 0.83 vs. 0.74). These results confirm H8 and H9. The path coefficient between the customer satisfaction and customer loyalty was positive and significant (β = 0.63 vs. 0.53). This study tested the suitability of two TCSI models by analyzing the tourism factories in Taiwan. The results showed that the TCSI models were all close fit for this type of research. This study provides empirical evidence of the causal relationships among perceived quality, image, perceived value, perceived expectations, customer satisfaction, and customer loyalty.

To observe the effects of antecedent constructs of perceived value (e.g., customer expectation and perceived quality), customer expectations were not significantly related to perceived value for either satisfied or dissatisfied customers. Furthermore, satisfied customers were affected more by perceived quality (β = 0.83 vs. 0.74), as shown in Table  1 . Regarding the effect of the antecedents of customer satisfaction (e.g., image, customer expectations, perceived value and perceived quality), the total effects of perceived quality on the customer satisfaction of satisfied and dissatisfied customers were 0.92 and 0.72. The total effects of image on the customer satisfaction of satisfied and dissatisfied customers were 0.45 and 0.19. Thus, the satisfaction level of satisfied customers was affected more by perceived quality. Consequently, regarding customer satisfaction, perceived quality is more important than image for satisfied and dissatisfied customers. Numerous researchers have emphasized the importance of service quality perceptions and their relationship with customer satisfaction by applying the CSI model (e.g., Ryzin et al. 2004 ; Hsu 2008 ; Yazdanpanah et al. 2013 ; Chiu et al. 2011 ; Temizer and Turkyilmaz 2012 ; Mutua et al. 2012 ; Dutta and Singh 2014 ). This is consistent with the results of previous research ( O’Loughlin and Coenders 2002 ; Yazdanpanah et al. 2013 ; Chiu et al. 2011 ; Chin and Liu 2015 ; Chin et al. 2016 ).

With respect to the effect of the antecedents of customer loyalty (e.g., image and customer satisfaction), the total effects of image on customer loyalty for satisfied and dissatisfied customers were 0.57 and 0.21. In other words, the customer loyalty of satisfied customers was affected more by customer satisfaction. Customer satisfaction was significantly related to the customer loyalty of both satisfied and dissatisfied customers, and satisfied customers were affected more by customer satisfaction ( β  = 0.63 vs. 0.14). Consequently, regarding customer loyalty, customer satisfaction is more important than image for both satisfied and dissatisfied customers. Numerous studies have shown that customer satisfaction is a crucial factor for ensuring customer loyalty (Barsky 1992 ; Smith and Bolton 1998 ; Hallowell 1996 ; Grønholdt et al. 2000 ). This study empirically supports the notion that customer satisfaction is positively related to customer loyalty.

The TCSI model has a predictive capability that can help tourism factory managers improve customer satisfaction based on different performance levels. Our model enables managers to determine the specific factors that significantly affect overall customer satisfaction and loyalty within a tourism factory. This study also helps managers to address different customer segments (e.g., satisfied vs. dissatisfied); because the purchase behaviors of customers differ, they must be treated differently. The contribution of this paper is to propose two satisfaction levels of CSI models for analyzing customer satisfaction and loyalty, thereby helping tourism factory managers improve customer satisfaction effectively.

Fornell et al. ( 1996 ) demonstrated that the ability to explain influential latent variables in a model, particularly customer satisfaction and customer loyalty variables, is an indicator of model performance. However, the results of this study indicate that customer expectations were not significantly related to perceived value for either satisfied or dissatisfied customers. Moreover, they were affected more by perceived quality of customer satisfaction. Numerous researchers have found that the construct of customer expectations used in the ACSI model does not significantly affect the level of customer satisfaction (Johnson et al. 1996 , 2001 ; Martensen et al. 2000 ; Anderson and Sullivan 1993 ).

Through the overall effects, this study derived several theoretical findings. First, the factors with the largest influence on customer satisfaction were perceived quality and perceived expectations, despite the results showing that customer expectations were not significantly related to perceived value or customer satisfaction. Hence, customer expectations indirectly affected customer satisfaction through perceived quality. Accordingly, perceived quality had the greatest influence on customer satisfaction. Likewise, our results also show that satisfied customers were affected more by perceived quality than dissatisfied customers. This study determined that perceived quality, whether directly or indirectly, positively influenced customer satisfaction. This result is consistent with those of Cronin and Taylor ( 1992 ), Cronin et al. ( 2000 ), Hsu ( 2008 ), Ladhari ( 2009 ), Terblanche and Boshoff ( 2010 ), Deng et al. ( 2013 ), and Yazdanpanah et al. ( 2013 ).

Second, the factors with the most influence on customer loyalty were image and customer satisfaction. The results of this study demonstrate that the customer loyalty of satisfied customers was affected more by customer satisfaction. Consequently, regarding customer loyalty, customer satisfaction is more important than image for satisfied customers. Lee ( 2015 ) found that higher overall satisfaction increased the possibility that visitors will recommend and reattend tourism factory activities. Moreover, numerous studies have shown that customer satisfaction is a crucial factor for ensuring customer loyalty (Barsky 1992 ; Smith and Bolton 1998 ; Hallowell 1996 ; Su 2004; Deng et al. 2013 ). In initial experiments on ECSI, corporate image was assumed to have direct influences on customer expectation, satisfaction, and loyalty. Subsequent experiments in Denmark proved that image affected only expectation and satisfaction and had no relationship with loyalty (Martensen et al. 2000 ). In early attempts to build the ECSI model, image was defined as a variable involving not only a company’s overall image but products or brand awareness; thus image is readily connected with customer expectation and perception. Therefore, this study contributes to relevant research by providing empirical support for the notion that customer satisfaction is positively related to customer loyalty.

In addition to theoretical implications, this study has several managerial implications. First, the TCSI model has a satisfactory predictive capability that can help tourism factory managers to examine customer satisfaction more closely and to understand explicit influences on customer satisfaction for different customer segments by assessing the accurate causal relationships involved. In contrast to general customer satisfaction surveys, the TCSI model cannot obtain information on post-purchase customer behavior to improve customer satisfaction and achieve competitive advantage.

Second, this study not only indicated that each of the antecedent constructs had reasonable power to explain customer satisfaction and loyalty but also showed that perceived quality exerts the largest influence on the customer satisfaction of Taiwan’s tourism factory industry. Therefore, continually, Taiwan’s tourism factories must endeavor to enhance their customer satisfaction, ideally by improving service quality. Managers of Taiwan’s tourism factories must ensure that service providers deliver consistently high service quality.

Third, this research determined that the factors having the most influence on customer loyalty were image and customer satisfaction. Therefore, managers of Taiwan’s tourism factories should allow customer expectations to be fulfilled through experiences, thereby raising their overall level of satisfaction. Regarding image, which refers to a brand name and its related associations, when tourists regard a tourism factory as having a positive image, they tend to perceive higher value of its products and services. This leads to a higher level of customer satisfaction and increased chances of customers’ reattending tourism factory activities.

Different performance levels exist in how tourists express their opinions about various aspects of service quality and satisfaction with tourism factories. Customer segments can have different preferences depending on their needs and purchase behavior. Our findings indicate that tourists belonging to different customer segments (e.g., satisfied vs. dissatisfied) expressed differences toward service quality and customer satisfaction. Thus, the management of Taiwan’s tourism factories must notice the needs of different market segments to meet their individual expectations. This study proposes two satisfaction levels of CSI models for analyzing customer satisfaction and loyalty, thereby helping tourism factory managers improve customer satisfaction effectively. Compared with traditional techniques, we believe that our method is more appropriate for making decisions about allocating resources and for assisting managers in establishing appropriate priorities in customer satisfaction management.

Limitations and suggestions for future research

This study has some limitations. First, the tourism factory surveyed in this study was a food tourism factory operating in Taipei, Taiwan, and the present findings cannot be generalized to the all tourism factory industries. Second, the sample size was quite small for tourists (N = 242). Future research should collect a greater number of samples and include a more diverse range of tourists. Third, this study was preliminary research on tourism factories, and domestic group package tourists were a major source of the respondents. Future studies should collect data from international tourists as well.

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Authors’ contributions

Writing: S-CL; providing case and idea: Y-CL, Y-CW, Y-FH, C-HC; providing revised advice: S-BT, WD. All authors read and approved the final manuscript.

Acknowledgements

Department of Technology Management, Chung-Hua University, Hsinchu, Taiwan. This work was supported by University of Electronic Science Technology of China, Zhongshan Institute (414YKQ01 and 415YKQ08).

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Department of Technology Management, Chung-Hua University, Hsinchu, 300, Taiwan

Yu-Cheng Lee

Department of Business Administration, Chung-Hua University, Hsinchu, 300, Taiwan

Yu-Che Wang

PhD Program of Technology Management, Chung-Hua University, Hsinchu, 300, Taiwan

Shu-Chiung Lu & Chih-Hung Chien

Department of Food and Beverage Management, Lee-Ming Institute of Technology, New Taipei City, 243, Taiwan

Shu-Chiung Lu

Department of Business Administration, Lee-Ming Institute of Technology, New Taipei City, 243, Taiwan

Chih-Hung Chien

Department of Food and Beverage Management, Taipei College of Maritime Technology, New Taipei City, 251, Taiwan

Yi-Fang Hsieh

Zhongshan Institute, University of Electronic Science and Technology of China, Dongguan, 528402, Guangdong, China

Sang-Bing Tsai

School of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China

Law School, Nankai University, Tianjin, 300071, China

School of Business, Dalian University of Technology, Panjin, 124221, China

College of Business Administration, Dongguan University of Technology, Dongguan, 523808, Guangdong, China

Department of Psychology, Universidad Santo Tomas de Oriente y Medio Día, Granada, Nicaragua

School of Economics and Management, Shanghai Institute of Technology, Shanghai, 201418, China

Weiwei Dong

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Lee, YC., Wang, YC., Lu, SC. et al. An empirical research on customer satisfaction study: a consideration of different levels of performance. SpringerPlus 5 , 1577 (2016). https://doi.org/10.1186/s40064-016-3208-z

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Received : 25 April 2016

Accepted : 02 September 2016

Published : 15 September 2016

DOI : https://doi.org/10.1186/s40064-016-3208-z

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• Customer satisfaction
• Tourism factory industry
• Partial least squares
• Business management
• Service management