Competitive intelligence and its impact on innovations in tourism industry of China: An empirical research

Yanli Bao

doi:10.1371/journal.pone.0236412

. 2020 Jul 31;15(7):e0236412. doi: 10.1371/journal.pone.0236412

Competitive intelligence and its impact on innovations in tourism industry of China: An empirical research

Yanli Bao ^1,^*

Editor: Bing Xue²

PMCID: PMC7394418 PMID: 32735590

Abstract

Competitive intelligence (CI) has attracted much attention in innovation research, but most of existing literature studies CI in technological innovations in manufacturing industry, with little empirical research in context of service businesses. This paper first analyzes CI of service businesses and then uses covariance-based structural equation modeling (SEM) on a data of 333 got from the survey in tourism enterprises of east China to test the effect of customer CI, opponent CI, and supplier CI on service innovations in China’s service industry. Results show that opponent CI and supplier CI have positive influence on both exploratory and exploitative service innovation. Customer CI has more obvious positive influence on exploratory service innovation than on exploitative service innovation.

1 Introduction

A growing consensus recognizes that service firms have been found to rely heavily on information flows within and outside their boundaries, and non-R&D innovations which use much external knowledge [1–4]. During the last decade, organizations are changing their innovation manners from a completely in-house and closed way [5] to a more open and collaborative way that involves customers, suppliers, research institutes, and even competitors [6, 7]. Service firms also are likely to collaborate frequently with their customers and suppliers, which play a positive role on firm innovation performance [8, 9]. And service innovation is based on certain knowledge resources, information and technology. Thus, service firms have to carry out proper searching for, understanding and utilizing the latest CI. This practice has created a need for using competitive intelligence(CI) for innovation in service firms.

Previous studies have indicated that the more information about innovation the companies get, the more selections of innovation they will get and the more likely they are to succeed [10]. For innovation, knowledge and information is recognized as being a critical resource [11] and acquiring CI among organizations could effectively promote innovations [12].

Despite these significant contributions, studies that analyze CI and service innovation in service firms are still scarce [13]. Therefore, it is necessary to make novel theoretical and empirical investigations in this respect which will shed new light on the competitive behaviors of service firms. Complementary to most of the existing research, this study investigates the effects of CI on innovation of service business in considering customer, opponent and supplier CI as well as their mutual relations. We test our hypotheses by means of structure equation modeling using 333 data collected with a survey of tourism enterprises in east China. In the next section, the theoretical background and research hypotheses are illustrated, followed by the research method, data analysis, research results and discussions as the next several parts.

2 Theoretical background

2.1 Competitive intelligence

Society of Competitive Intelligence Professional (SCIP) is an authoritative body in CI. In 2003, it defined CI as the systematic and ethical collection, analysis and management of external information that can affect the planning, decision-making and business operation. CI has been listed as the fourth reason for the survival of enterprises after capital, technology and talent [14]. Entering the era of knowledge-based economy, the degree of informationization in China is getting higher and higher. Enterprise CI has gradually become one of the decisive factors for the survival and development of enterprises. In general, CI includes information about competitors, customers, suppliers and related technologies [15]. Beal(2000) regards enterprise's customer intelligence, supplier intelligence, opponent intelligence as the competitive environment in which the enterprise lives [16].

2.2 Service innovation

Innovativeness of enterprises refers to a “firm’s capacity to engage in innovation through the introduction of new processes, products, or ideas” [17]. Service innovation refers to innovation in the field of services, proposing new service concepts, carrying out new service processes, and applying new technologies to improve or change existing services, process and service products [18, 19].

Innovation can be classified into four types, i.e. product innovation, process innovation, organizational innovation and marketing innovation [20]. But according to the scope and knowledge base, innovation is divided into exploratory innovation and exploitative innovation [21, 22]. Exploratory innovation is a large-scale and radical innovation activity with the intention to find out new possibilities. Exploitative innovation is a small-scale and gradual innovation activity with the intention to improve the existing status [23]. Therefore, academia believes that service innovation can also be divided into exploratory service innovation and exploitative service innovation according to the classification of common innovation. Exploratory service innovation refers to serving customers through the use of disruptive or new technologies, new idea or new service process; Exploitative service innovation leverages current capabilities to develop products and services to serve customers better [24].

2.3 CI and service innovation

External consultants and knowledge acquisition on opponents, customers and suppliers all have effects on innovation activities and performance [25, 26]. Firms have recognized the importance of information acquired from competitors in the industry, and customer and suppliers [27]. Some scholars found that professional supplier information is the most effective in promoting innovation, and customer information is the most relevant to innovation process [28].

According to our observation on service businesses in China, we find that their innovation is also relying on these three kinds of CI. First, customer CI. Service firms often collect customer CI through customer visits, satisfaction feedback, and evaluation of existing services. The customer CI then will be used to improve services or explore new services. Second, opponent CI. Service firms get opponent CI about products/services, R&D, customers, marketing, cost, technology, which can help enterprises understand their strengths and weaknesses and analyze the differences between their own services and competitors’, and then innovate, imitate or launch innovative services with more advantages. Third, supplier CI. For service businesses, most technological innovations come from suppliers. Therefore, timely access to information on new products, technologies and ideas developed by suppliers can help firms to carry out service innovation as soon as possible.

Therefore, this paper divides CI that influences innovation in service businesses into three elements, namely, customer CI, opponent CI, and supplier CI. Based on the theory of service innovation and features of CI, this paper illustrates how different kinds of CI affect service innovation to reveal the mechanism of CI on service innovation.

2.3.1 Effect of customer CI on service innovation

Customer CI is the source of knowledge and information for service innovation, because products are ultimately customer-oriented. Customer demand promotes enterprises to open up new services or improve existing service technologies or product functions. Customers have the ability to influence innovation [29].

Based on the classification of customer knowledge by Zhang Hongqi and Lu Ruoyu [30], this paper divides customer CI into four main aspects, namely, basic customer CI, customer satisfaction CI, customer demand CI, and CI of customers’ participation in innovation. Firstly, basic customer CI and customer satisfaction CI play an active role in service innovation. When enterprises understand customer information, effectively convey customer opinions, and settle customer complaints, the number of service innovation will increase [31]. Secondly, in order to carry out innovations, enterprises must tap the potential needs of customers, collect and analyze their demand, which can help to identify market demand, generate new service concepts and products, and realize exploratory and exploitative service innovation. Thirdly, CI about customer participation in innovation is of positive significance to both exploratory and exploitative service innovation in forms of service interface, service delivery system and service technology. In the process of service innovation, customers can be cooperative designers or producers of new products and services [32].

Therefore, this paper proposes hypotheses:

H1: A higher emphasis on customer CI positively influences exploitative service innovation.
H2: A higher emphasis on customer CI positively influences exploratory service innovation.

2.3.2 Effect of Opponent CI on service innovation

Opponent analysis is the soul of CI [33]. Opponent CI refers to identifying competitors, analyzing their strength, predicting their strategies, especially evaluating their new products and main products in the aspects of price, cost, profit, development and design ability, marketing strategy as well as opponent’s strengths, weaknesses and their recognition of customer needs [34].

Opponent CI in service businesses can be classified into three main aspects, i.e. Opponents’ daily operation CI, R&D CI and marketing CI of new services. Through opponent CI, enterprises can also grasp their latest developments, especially CI about new products and new services development, which is conducive to enterprises’ imitative innovation, which is a major form of exploitative service innovation. Enterprises can optimize their own knowledge resources and improve service by learning from their opponents [35]. They can also realize exploratory service innovation through developing new products and technology with the help of opponent CI.

Based on this, this paper proposes the following hypotheses:

H3: A higher emphasis on opponent CI positively influences exploitative service innovation.
H4: A higher emphasis on opponent CI positively influences exploratory service innovation.

2.3.3 Effect of supplier CI on service innovation

Suppliers have a crucial role in improving firms’ innovation performance [36, 37]. Supplier involvement into innovation processes has been recognized as a potential source of sustainable competitive advantage, even though the literature is not fully consistent. Supplier is one of the major innovation drivers of Italian service businesses [38]. It is also one of the sources of service innovation and has a positive impact on enterprise innovation activities. In some industries, such as tourism industry and hotel industry, technological innovation is mainly dominated by suppliers [39].

Suppliers affect the types of innovation. In the context of emerging economy, local suppliers’ absorptive capacity is critically important in spurring exploitative and exploratory innovation [40]. Suppliers can not only introduce new materials and technologies into existing products and services to meet current needs, but also help enterprises develop new products and services [41]. Suppliers’ participation in service innovation can provide innovative ideas, key technologies, raw materials and so on [42]. In addition, suppliers are innovative and their activities such as developing new production methods, adopting new processes, raw materials, new technologies or applying new business models have a positive impact on product and service innovation [43]. Suppliers’ contribution assumes various forms, such as supply of innovative components and product/process technologies, or joint product development projects [44]. Moreover, the inventory CI and marketing CI of suppliers have a tremendous impact on enterprises’ daily operations. And their price changes and shortages of raw materials, equipment, technology and human resources will also affect whether enterprises can carry out exploratory and exploitative service innovation or not.

Based on this, this paper proposes:

H5: A higher emphasis on supplier CI positively influences exploitative service innovation.
H6: A higher emphasis on supplier CI positively influences exploratory service innovation.

3. Methodology

3.1. Ethics statement

The study was approved and supported by the institutional review board of Wuxi Tourism Association, Jiangsu, China. The subject of this manuscript is CI and service innovation situation in companies rather than human beings. All people interviewed with the questionnaire provided their consent by answering the questions. Their names and personal information are kept secret. Therefore, they are free to express their feelings about the CI and service innovation in their companies.

3.2. Data collections

To test the hypotheses and the model, they had to be converted into a questionnaire. Each construct is represented by a set of indicators which form the questions in the survey. All questions were measured on a positive-to-negative 7-point Likert scale. Questions on the CI and service innovation give a statement and ask for the level of agreement on the following scale: "Strongly agree—predominantly agree—rather agree—neutral—rather disagree—predominantly disagree—strongly disagree." The questionnaire was discussed intensively within our research institute and pre-tested independently with 5 managers from service businesses which were not included in the sample. These 5 managers all have more than 10 years working experiences in star hotels, travel agencies, tourist attractions, or other service companies. Based on the discussions, the questionnaire was modified.

The firms selected for this study are employees of star hotels and tourism companies of more than 20 staff in China, because tourism industry has the typical characteristics of service industry and a huge amount in China.

Data was collected in two stages. First, in pre-survey, 100 questionnaires were distributed and 94 valid questionnaires were returned. In pre-survey, Cronbach’s alpha coefficient and factor load of the scale were calculated by SPSS 23 software, and the item was deleted according to relevant standards. Second, with the refined questionnaire, the investigator gets approval from the administrators of tourism companies and sends an invitation letter out through e-mail to express the need for collection of empirical data concerning service innovation experience in using CI. The administrators then forwarded the message to their staff via email and instructed the receivers to click a hyperlink and redirected them to an online questionnaire system. Consequently, 400 invitation letters were sent to the staff in tourism industry through e-mail. In order to improve the return rate, another follow-up invitation letter was sent to non-responding staff with the same aforementioned procedure after a week. Finally, 362 staff had finished and returned the questionnaire. Altogether 333 valid questionnaires were obtained after deleting unqualified questionnaires, with an effective return rate of 83.25%.

3.3. Measures

Measurement items were selected based on a careful literature review. The results from pre-survey showed that there is no bias.

The scale of enterprise CI is modified by the relevant scales used in empirical researches. The scale of customer CI is made by revising Zhang Hongqi and his partners’ scale (2013) [45]. Four items were adapted to measure the extend of customer CI(CCI), including basic customer information, customer demand, customer satisfaction and customer participation in innovation. The opponent intelligence (OCI) scale is prepared in 3 aspects, i.e. competitor’s daily operation CI, R&D CI and marketing CI of new services. The scale of supplier CI(SCI) is developed on the basis of Gales, Mansour-Cole (1995) [46] and interviews with service business owners. Three are 3 items describing supplier CI including supplier inventory, R&D, and marketing.

The scale of service innovation adopts the scale of exploitative innovation(ETSI) and exploratory innovation(ERSI) developed by Fu Xiao et al. (2012) [47] to assess the extent to which a firm has engaged in innovation activities and has implemented service innovation activities to improve existing service–market positions with 8 items.

4. Data analysis

The data analysis of this study was conducted using structural equation modeling (SEM) technique and followed the two-step approach of for assessing the measurement and structural models respectively [48]. SEM is a powerful statistical research technique and it is very flexible in the types of theoretical models to be tested for analyzing the causal relationships between multiple-item constructs [49]. In addition, SPSS and AMOS are adopted as the tools of data analysis.

4.1 Instrument validation

An initial exploratory factor analysis is carried out to verify the internal structure of variables. And the confirmatory factor analysis is made on three dimensions of enterprise CI and two kinds of service innovation to evaluate their fitness. We selected 121 questionnaires randomly from valid questionnaires for exploratory factor analysis in order to test reliability and validity.

Firstly, exploratory factor analysis is carried out on “Enterprise CI”. KMO = 0.742, greater than 0.7, and Bartlett statistic is significantly equal to 0. 000 at 45 degrees of freedom, which is suitable for factor analysis.

Component matrix after rotation of each factor is shown on Table 1. According to the requirement that the characteristic root is greater than 1 and the maximum factor load is greater than 0.5, the factor load of CCI1 (basic customer CI) in the original scale is less than 0.5, which indicates that the measurement information of this item is not accurate enough, so it is removed from the scale.

Table 1. Component matrix after rotation of enterprise CI (N = 121).

	Component
	1	2	3
CCI1	-.133
CCI2	.953
CCI3	.932
CCI4	.911
OCI1		.963
OCI2		.978
OCI3		.943
SCI1			.940
SCI2			.947
SCI3			.922

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The results of exploratory factor analysis on the scale which has removed Basic Customer CI(CCI1) shows that each item is distributed in three factors according to expectation, and the factor load has a good distinction among the three factors. Thus, the new revised scale of the “Enterprise CI” has a good validity.

Next, the reliability of each factor is analyzed to test the internal consistency among the items that passed the exploratory factor analysis. The results show that the overall correlation coefficients of all items are greater than 0.8, and the Cronbach Alpha coefficients of all variables are greater than 0.8. Therefore, there is good internal consistency among the items of the variables of “Enterprise CI”.

Secondly, exploratory analysis is made on “service innovation”. KMO = 0.833. As shown on Table 2, two factors are extracted according to the requirement that the characteristic root should be greater than 1 and the maximum factor load is greater than 0.5.

Table 2. Component matrix after rotation of service innovation (N = 121).

	Component
	1	2
ETSI1	.779
ETSI2	.839
ETSI3	.905
ETSI4	.826
ERSI1		.786
ERSI2		.836
ERSI3		.682
ERSI4		.801

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Next, the reliability of each factor is analyzed to test the internal consistency among the items. The results show that the overall correlation coefficient of all items is greater than 0.6, and the Cronbach Alpha coefficient of each variable is greater than 0.7. Therefore, there is good internal consistency among the items of the variables of service innovation.

Thirdly, the confirmatory factor analysis is done using the remaining 212 samples to ensure that the factor structure of all variables tested is consistent with the previous concepts. The reliability of customer CI, opponent CI, supplier CI, exploratory and exploitative service innovations are analyzed. The results are as shown on Table 3 that each variable index meets the reliability index requirements mentioned above and passes the reliability test. Thus, we can be sure that the consistency of variable measures is good.

Table 3. Reliability test of CI and service innovation (N = 212).

	Corrected item and total correlation	Cronbach Alpha of Corrected item	Cronbach Alpha
CCI2	.824	.872
CCI3	.841	.858	.912
CCI4	.805	.888
OCI1	.807	.888
OCI2	.854	.849	.913
OCI3	.812	.884
SCI1	.823	.875	.911
SCI2	.870	.833
SCI3	.780	.906
ERSI1	.770	.908
ERSI2	.852	.883	.918
ERSI3	.866	.880
ERSI4	.785	.903
ETSI1	.842	.896
ETSI2	.831	.900	.924
ETSI3	.831	.900
ETSI4	.800	.910

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Then the initial structural equation model is analyzed and calculated by AMOS software. The results of enterprise CI are: CMIN/DF = 2.582, GFI = 0.940, NFI = 0.958, RFI = 0.937, IFI = 0.974, TLI = 0.961, CFI = 0.974, all greater than 0.9, close to 1, RMSEA = 0.087, less than 0.1. The path coefficients are statistically significant at the level of P < 0.001(see Table 4). The results of “service innovation” are CMIN/DF = 2.721. GFI = 0.941, NFI = 0.964, RFI = 0.947, IFI = 0.977, TLI = 0.966, CFI = 0.977, all close to 1; RMSEA = 0.09, close to 0; the path coefficients are statistically significant at the level of P < 0.001(see Table 5). This factor structure has passed the validation. This study is effective in dividing and measuring all the variables.

Table 4. Measurement model fitting results of enterprise competitive intelligence (N = 212).

		Estimate	S.E.	C.R.	P
CCI3	CCI	1.000
CCI2	CCI	1.137	.069	16.572	***
CCI1	CCI	1.101	.067	16.403	***
OCI3	OCI	1.000
OCI2	OCI	1.052	.058	18.086	***
OCI1	OCI	.958	.059	16.132	***
SCI3	SCI	1.000
SCI2	SCI	1.143	.069	16.454	***
SCI1	SCI	1.233	.077	16.019	***

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Table 5. Measurement model fitting results of service innovation (N = 212).

			Estimate	S.E.	C.R.	P
ETSI1	<—	ETSI	1.000
ETSI2	<—	ETSI	.964	.055	17.547	***
ETSI3	<—	ETSI	1.113	.060	18.440	***
ERSI1	<—	ERSI	1.000
ERSI2	<—	ERSI	1.301	.082	15.862	***
ERSI3	<—	ERSI	1.024	.064	16.005	***
ERSI4	<—	ERSI	1.073	.076	14.114	***
ETSI4	<—	ETSI	1.025	.063	16.324	***

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4.2 Assessing the hypotheses

This paper performs structural equation modeling (SEM) to test the research model and the hypotheses. The initial structural equation model is analyzed and calculated by AMOS software. The fitting results were CMIN/DF = 2.626, GFI = 0.861, NFI = 0.911, RFI = 0.889, IFI = 0.943, TLI = 0.929, CFI = 0.942, RMSEA = 0.088. On Table 6, it can be seen hypothesis 2 is that customer intelligence has a significant positive impact on exploratory service innovation is confirmed; hypothesis 3 and 4 are confirmed, indicating that opponent CI has a significant positive impact on exploratory and exploitative service innovation; hypothesis 5 and 6 are also confirmed that supplier CI has a significant positive impact on exploratory and exploitative service innovation. However, hypothesis 1 that customer CI has positive effect on exploitative service innovation is not confirmed. According to the opinions of many respondents, service businesses are more likely to use customer CI to develop new services to meet their needs. In exploitative innovations, they are inclined to adapt supplier and opponent CI in order to avoid innovation failure. Thus, compared with exploratory service innovation, the positive impact of customer intelligence on exploitative service innovation is not significant.

Table 6. Non-standardized regression coefficient.

			Estimate	S.E.	C.R.	P
ERSI	<—	CCI	.247	.062	3.984	***
ERSI	<—	OCI	.163	.048	3.416	***
ERSI	<—	SCI	.298	.071	4.174	***
ETSI	<—	CCI	.150	.056	2.670	.008
ETSI	<—	OCI	.265	.045	5.908	***
ETSI	<—	SCI	.262	.065	4.023	***

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5. Discussion and implication

5.1 Conclusions

In the process of innovation in service businesses, CI plays an important role. Through empirical research, this paper proves that three dimensions of enterprise CI have different influences on service innovation. Customer CI has stronger effect on exploratory service innovation than on exploitative service innovation. Opponent CI and supplier CI have obvious positive effects on both exploratory and exploitative service innovation.

5.2 Theoretical contributions

This study is a pioneer to examine how different dimensions of CI generate direct effects on innovation in service firms. While many previous studies often link customer CI, supplier CI to service innovation [50–52] without taking opponent CI into consideration, this study has proposed effects of opponent CI on exploratory and exploitative service innovation. Our empirical testing has found the effect of opponent CI to be strongly supported, with the two paths significant in the hypothesized directions. As a result, this contributes to the development of a more comprehensive account of opponents’ behavior.

A recent study by Mohan and his partners [53] has also highlighted the important role of suppliers in service innovation process. Indeed, the inclusion of supplier knowledge and technology in any theoretical model to predict innovations is strongly warranted. Besides, not unexpected, customer CI has a significant effect on exploratory service innovation. This finding is consistent with prior results in literature about customer knowledge and innovation [54–56]. But its positive effect on exploitative service innovation is not strong. This result would be a complementary for previous literature of customer and service innovation.

5.3 Practical contributions

Based on the empirical research results of tourism service industry with typical service characteristics, this paper provides the following management enlightenment for China’s service industry in using CI to improve service innovation.

CI is an indispensable motive force and source of service innovation in an industry as a whole or in an individual enterprise. Application of CI has a positive influence on both exploratory and exploitative service innovation.
For service enterprises, customer is God, who is the purchaser of products and services. All information about customers’ consumption demand, satisfaction and other aspects is essential for the survival and development of new products and services. By analyzing customers’ past purchasing and potential customer needs through interactive platforms, customer visits or market surveys, enterprises will make progress in service innovation. Customers’ previous purchasing and potential demand can help enterprises develop new services and try new fields.
Opponent CI which has always been the focus of managers and scholars plays a key role in the survival, development and innovation of service enterprises. It is indispensable for enterprises to acquire and analyze opponent CI. Competitors’ new products and services can become the object of imitation and inspiration source of exploitative service innovation. For service enterprises, imitating competitors has the advantages of less investment, higher efficiency and less risk. Therefore, many service enterprises usually start their own innovation activities by imitating competitors.
Suppliers are important partners. New technology and knowledge are both sources for service innovation. Some service industries, such as hotels, are mainly supplier-led in technological innovation [39]. Suppliers can provide enterprises with new service production and process control solutions, tools and equipment needed for new services. Therefore, it is necessary to select innovative suppliers and strengthen cooperation and exchanges with them.

5.4 Limitations and future research

Firstly, this study got data mainly from tourism enterprises, such as tourist attractions, hotels, food and crafts companies, travel agencies and so on. This study considers tourism enterprise as typical service businesses; therefore, it does not consider the different features of sub-types of service enterprises. Secondly, this study is conducted in east China, which has a unique cultural and economic environment in China. The generalizability of our findings to China’s service enterprises will need to be confirmed with additional studies in different places to take account of the differences in culture and economy. In the future, further researches about service innovations of different types of service enterprises in different places are need.

Supporting information

S1 Data. English and Chinese quesitonnarie.

(DOCX)

Click here for additional data file.^{(19.4KB, docx)}

S2 Data. Ethical statement.

(DOCX)

Click here for additional data file.^{(14.1KB, docx)}

S3 Data. CI&SI(confimatory and amos-212).

(SAV)

Click here for additional data file.^{(5.1KB, sav)}

S4 Data. CI&SI(exploratory-121).

(SAV)

Click here for additional data file.^{(4.3KB, sav)}

Acknowledgments

We thank Cheng Changchun and Hua Hefeng for valuable research assistance.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This research is supported by Philosophy and Social Science Foundation of 2014 China National Education Department.

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PLoS One. doi: 10.1371/journal.pone.0236412.r001

Decision Letter 0

Bing Xue

19 Mar 2020

PONE-D-20-03099

Competitive Intelligence and Its impact on Innovations in Tourism Industry of China: an Empirical Research

PLOS ONE

Dear Dr. Bao,

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The language needs to be modification. it is difficult to understand the author's meaning now.

The introduction of Literature review on CI is incomprehensive. What is the author's contribution?

The format of references cited in the paper is inconsistent, such as the second page Zhao chen2014.

Citation: Most of the literature is older and lacks of the latest research tracking.

Theoretical background: The description is lacking of logic. What is the author's intention to write this part?

Why are the hypothesis settings the same?How to distinguish in the questionnaire needs to be explained.

Method section: How are the 20 samples selected for the survey? Why is the survey designed at 7 latitudes? Who is the target of the survey? Data processing needs to be described in more detail.

The structural equation model mentioned in the abstract requires detailed to explain the research design of the method in the method section.

There is too little analysis of the results, the conclusions of the study design are not thoroughly analyzed, and there is little analysis related to the CI theme.

The discussion part is more like a conclusion. The discussion needs to be re-associated with the current research frontier and the research results obtained in this paper for a targeted discussion.

Reviewer #2: The facts given in the manuscript are already well known. I am unable to figure out any novel contribution. Secondly manuscript is organized poorly. For instance, 'Keywords' is just one word not two. After starting Section 3, authors immediately started subsection 3.1 without any content in Section 3.

Reviewer #3: 1. All discussion is too general without any comparison. I suggest authors should compare your results with others’ reports so as to find different conclusion.；

2. please have the paper thoroughly edited to address some grammatical errors that exist throughout the paper；

3. The authors state this approach is first used in this research field, How? There is no evidence in this paragraph

4. Where is the discussion of this literature? This is important.

**********

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PLoS One. 2020 Jul 31;15(7):e0236412. doi: 10.1371/journal.pone.0236412.r002

Author response to Decision Letter 0

28 May 2020

Response to editor’s Comments

First of all, thank you very much for your very encouraging and inspiring feedback on my work and for your very constructive and helpful comments that have definitely improved the paper a great deal. I had studied all of your comments very carefully and tried to incorporate all of them into the current version of the paper. Please find more detailed descriptions of how I did that below. I have modified my paper to accommodate your concerns (major changes in the article are written as notes in the margin on each page for your quick perusal). In addition, I provided a point-by-point response to each of your comment. For ease of distinction, your originals comments are listed below in regular font, and my responses to those comments are shown in italics font.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Thank you very much for your information. I have edited my manuscript following PLOS ONE's style requirements.

Thanks deeply for your suggestion. In section 3.1(Data collections), I have specified the participant consents. You can find:

“Second, with the refined questionnaire, the investigator gets approval from the administrators of tourism companies and sends an invitation letter out through e-mail to express the need for collection of empirical data concerning service innovation experience in using CI. The administrators then forwarded the message to their staff via email and asked the receivers to click a hyperlink and redirected them to an online questionnaire system. Consequently, 400 invitation letters were sent to the staff in tourism industry through e-mail. In order to improve the return rate, another follow-up invitation letter was sent to non-responding staff with the same aforementioned procedure after a week. Finally, 362 staff had finished and returned the questionnaire.

Following your suggestion, I added detailed description of methodology to section 3 Methodology and a questionnaire in both Chinese and English as supporting information.

Thank you for your insightful comment. I checked the tables and re-order them. Now I can ensure that all the tables are referred to in the manuscript.

Response to Reviewer 1’s Comments

Reviewer #1: The language needs to be modification. it is difficult to understand the author's meaning now.

Thanks deeply for your suggestion. I have refined the sections of literature review, methodology, data analysis and discussion. Furthermore, in this revision, grammatical and writing style errors in the original version have been refined and edited by my friend who is a native English speaker.

The introduction of Literature review on CI is incomprehensive. What is the author's contribution?

Thank you very much for your inspiring feedback. I rewrote this part and included the definition of CI, its importance and contents, which are the basis of research framework and hypotheses. I simplified the expressions so that this part is comprehensible. The relevant content is shown as follows.

Society of Competitive Intelligence Professional (SCIP) is an authoritative body in CI. In 2003, it defined CI as the systematic and ethical collection, analysis and management of external information that can affect the planning, decision-making and business operation. CI has been listed as the fourth reason for the survival of enterprises after capital, technology and talent[ ]. Entering the era of knowledge-based economy, the degree of informationization in China is getting higher and higher. Enterprise CI has gradually become one of the decisive factors for the survival and development of enterprises. Generally speaking, CI includes information about competitors, customers, suppliers and related technologies[ ]. Beal(2000) regards enterprise's customer intelligence, supplier intelligence, opponent intelligence as the competitive environment in which the enterprise lives[ ].

The format of references cited in the paper is inconsistent, such as the second page Zhao chen2014.

Thanks deeply for your inspection. I fixed this typing mistake in this new version. And I consulted the editor for the format of references and changed it. You can check it in the references of revised manuscript.

Citation: Most of the literature is older and lacks of the latest research tracking.

Thanks for your helpful feedback. I have updated and cited the recent relevant publications including Barão, de Vasconcelos, Rocha, & Pereira(2017) ,Thornhill(2019);Urbinati, A., Chiaroni, D., Chiesa, V., Frattini, F., 2018; Melton, H. L., & Hartline, M. D. (2013); Kratzer, J., Meissner, D., Roud, V.(2017);Bianchi et al.(2016); Berchicci(2013). All of them are listed in the reference section.

Theoretical background: The description is lacking of logic. What is the author's intention to write this part?

Thanks for your insightful comment. According to your comment, I rewrote the section 2(Theoretical background). In this section, I first introduced the literature about 2.1(competitive intelligence) and 2.2(service innovation), then analyzed existing research findings about the relationship between them(2.3 CI and Service Innovation) in order to find out the research gap and lay the groundwork for making hypotheses. I hope you will find these changes in this section as corresponding to your helpful comment.

Why are the hypothesis settings the same?How to distinguish in the questionnaire needs to be explained.

Thank you for your insightful questions. The hypotheses settings are the same because I want to keep in the same style to express to relationship between CI and service innovation so that the readers can understand the hypotheses easily. In the questionnaire, I explain each variable clearly and the questionnaire was discussed intensively within our research institute and pre-tested independently with 5 managers from service businesses which were not included in the sample. These 5 managers all have more than 10 years working experiences in star hotels, travel agencies, tourist attractions, or other service companies. Based on the discussions, the questionnaire was modified. All the variables in both Chinese and English are listed here for your reference:

Customer CI refers to the competitive intelligence about customers: 顾客情报是指与顾客有关的竞争情报。

CCI1 We collect basic information of customers, including their name, age, occupation/profession,et.al. 我们收集客户的基本信息，包括他们的姓名、年龄、职业等。

CCI2 We collect and analyze customer need/demand about our services.我们收集并分析客户对我们服务的需求。

CCI3 We collect and analyze customer satisfaction and customer complaints.我们收集和分析客户满意度和客户投诉情况。

CCI4 We invite customers to participate in service innovation.我们邀请客户参与服务创新。

Opponent CI refers to the competitive intelligence about opponents:竞争对手情报是指关于竞争对手的情报：

OCI1 We collect and analyze opponents’ daily operation information. 我们收集并分析对手的日常运营信息。

OCI2 We keep eyes on R&D progress of our opponents.我们关注对手的研发进展。

OCI3 We pay attention to marketing of the new services/products from our opponents. 我们关注对手推销新服务/产品的情报。

Supplier CI refers to the competitive intelligence about suppliers:供应商情报是指关于供应商的竞争情报：

SCI1 We collect and analyze information about inventory of suppliers’ service/products.我们收集和分析有关供应商服务/产品库存的信息。

SCI2 We collect and analyze information about R&D of new service/products of suppliers.我们收集和分析供应商新服务/产品的研发信息。

SCI3 We collect and analyze information about marketing of service/products supplied by our suppliers. 我们收集并分析供应商提供的服务/产品的市场信息。

Exploitative service innovation(ETSI) refers to a small-scale and gradual innovation activity with the intention to improve the existing status. 利用式服务创新是一种小幅度、渐进的创新活动，其意图是对服务现状进行改进。

ETSI1 We make efforts to improve the applicability of existing service/skills in many related business areas.我们努力提高已有的技术/技能在多个相关业务领域的适用性。

ETSI2 We often use existing service/skills to increase the functions and types of products/services. 我们经常利用已有的技术/技能来增加产品/服务的功能和种类。

ETSI3 We often improve existing service/skills to meet current needs.我们经常对已有的技术/技能进行改良，以适应当前需要。

ETSI4 We often refine our accumulated business experience and applies it to the current business. 我们经常对公司积累的业务经验进行提炼，并应用于当前业务中。

Exploratory Service innovation(ERSI) refer to a large-scale and radical innovation activity with the intention of finding new possibilities. 探索式创新是一种大幅度的、激进的创新活动，其意图是寻找新的可能性。

ERSI1 We frequently develop brand-new market segments without relevant marketing experience. 我们经常开拓全新的、尚无相关营销经验的细分市场。

ERSI2 We often adopt business strategies/tactics that have not been adopted by other companies in the same industry. 我们经常采用同行业其他公司没有采用过的经营战略/战术。

ERSI3 We frequently use immature and risky new services/skills. 我们经常运用尚不成熟、有一定风险的新技术/技能。

ERSI4 We frequently develop new and radical products/services. 我们经常开发全新的、根本性变革的产品/服务。

Method section: How are the 20 samples selected for the survey? Why is the survey designed at 7 latitudes? Who is the target of the survey? Data processing needs to be described in more detail.

Thank you very much for your inspiring questions and suggestions. According to your suggestions, I rewrote section 3(Methodology） . I added how each construct is measured by questions in the survey, how the questions are modified, the targets of the survey and how the survey is delivered in service firms. The data processing is also described in Data Analysis section. The relevant content is shown as follows:

3.Methodology

3.1. Data collections

To test the hypotheses and the model, they had to be converted into a questionnaire. Each construct is represented by a set of indicators which form the questions in the survey. All questions were measured on a positive-to-negative 7-point Likert scale. Questions on the CI and service innovation give a statement and ask for the level of agreement on the following scale: "Strongly agree - predominantly agree - rather agree - neutral - rather disagree - predominantly disagree - strongly disagree." The questionnaire was discussed intensively within our research institute and pre-tested independently with 5 managers from service businesses which were not included in the sample. These 5 managers all have more than 10 years working experiences in star hotels, travel agencies, tourist attractions, or other service companies. Based on the discussions, the questionnaire was modified.

3.2. Measures

Measurement items were selected on the basis of a careful literature review. The results from pre-survey showed that there is no particular bias. A description of the constructs and indicators is presented in Appendix 1.

The scale of enterprise CI is modified by the relevant scales used in empirical researches. The scale of customer CI is made by revising Zhang Hongqi and his partners’ scale (2013)[ ]. Four items were adapted to measure the extend of customer CI(CCI), including basic customer information, customer demand, customer satisfaction and customer participation in innovation. The opponent intelligence(OCI) scale is prepared in 3 aspects, i.e. competitor’s daily operation CI, R&D CI and marketing CI of new services. The scale of supplier CI(SCI) is developed on the basis of Gales, Mansour-Cole (1995)[ ] and interviews with service business owners. Three are 3 items describing supplier CI including supplier inventory, R&D, and marketing.

The scale of service innovation adopts the scale of exploitative innovation(ETSI) and exploratory innovation(ERSI) developed by Fu Xiao et al. (2012)[ ] to assess the extent to which a firm has engaged in innovation activities and has implemented service innovation activities to improve existing service–market positions with 8 items.

4. Data Analysis

The data analysis of this study was conducted using structural equation modeling (SEM) technique and followed the two-step approach of for assessing the measurement and structural models respectively[ ]. SEM is a powerful statistical research technique and it is very flexible in the types of theoretical models to be tested for analyzing the causal relationships between multiple-item constructs[ ]. In addition, SPSS and AMOS are adopted as the tools of data analysis.

The structural equation model mentioned in the abstract requires detailed to explain the research design of the method in the method section.

Thank you for your suggestion. I added content about SEM in Section 4 (Data analysis).The relevant content is shown as follows: The data analysis of this study was conducted using structural equation modeling (SEM) technique and followed the two-step approach of for assessing the measurement and structural models respectively[ ]. SEM is a powerful statistical research technique and it is very flexible in the types of theoretical models to be tested for analyzing the causal relationships between multiple-item constructs[ ]. In addition, SPSS and AMOS are adopted as the tools of data analysis.

There is too little analysis of the results, the conclusions of the study design are not thoroughly analyzed, and there is little analysis related to the CI theme.

The discussion part is more like a conclusion. The discussion needs to be re-associated with the current research frontier and the research results obtained in this paper for a targeted discussion.

Thanks for your helpful comment and suggestion. I rewrote the relevant contents and associated my results with the current research findings. The relevant contents are as follows:

5. Discussion And Implication

5.1 Conclusions

5.2 Theoretical contributions

This study is a pioneer to examine how different dimensions of CI generate direct effects on innovation in service firms. While many previous studies often link customer CI, supplier CI to service innovation[ ],[ ],[ ] without taking opponent CI into consideration, this study has proposed effects of opponent CI on exploratory and exploitative service innovation. Our empirical testing has found the effect of opponent CI to be strongly supported, with the two paths significant in the hypothesized directions. As a result, this contributes to the development of a more comprehensive account of opponents’ behavior.

A recent study by Mohan and his partners[ ]has also highlighted the important role of suppliers in service innovation process. Indeed, the inclusion of supplier knowledge and technology in any theoretical model to predict innovations is strongly warranted. Besides, not unexpected, customer CI has a significant effect on exploratory service innovation. This finding is consistent with prior results in literature about customer knowledge and innovation[ ],[ ],[ ]. But its positive effect on exploitative service innovation is not strong. This result would be a complementary for previous literature of customer and service innovation.

5.3 Practical contributions

(1) CI is an indispensable motive force and source of service innovation in an industry as a whole or in an individual enterprise. Application of CI has a positive influence on both exploratory and exploitative service innovation.

(2) For service enterprises, customer is God, who is the purchaser of products and services. All information about customers’ consumption demand, satisfaction and other aspects is essential for the survival and development of new products and services. By analyzing customers’ past purchasing and potential customer needs through interactive platforms, customer visits or market surveys, enterprises will make progress in service innovation. Customers’ previous purchasing and potential demand can help enterprises develop new services and try new fields.

(3) Opponent CI which has always been the focus of managers and scholars plays a key role in the survival, development and innovation of service enterprises. It is indispensable for enterprises to acquire and analyze opponent CI. Competitors’ new products and services can become the object of imitation and inspiration source of exploitative service innovation. For service enterprises, imitating competitors has the advantages of less investment, higher efficiency and less risk. Therefore, many service enterprises usually start their own innovation activities by imitating competitors.

(4) Suppliers are important partners. New technology and knowledge are both sources for service innovation. Some service industries, such as hotels, are mainly supplier-led in technological innovation[ ]. Suppliers can provide enterprises with new service production and process control solutions, tools and equipment needed for new services. Therefore, it is necessary to select innovative suppliers and strengthen cooperation and exchanges with them.

5.4 Limitations and future research

Firstly, this study got data mainly from tourism enterprises, such as tourist attractions, hotels, food and crafts companies, travel agencies and so on. This study considers tourism enterprise as typical service businesses, therefore, it does not consider the different features of sub-types of service enterprises. Secondly, this study is conducted in east China, which has a unique cultural and economic environment in China. The generalizability of our findings to China’s service enterprises will need to be confirmed with additional studies in different places to take account of the differences in culture and economy. In the future, further researches about service innovations of different types of service enterprises in different places are need.

Response to Reviewer 2’s Comments

First of all, thank you very much for your very encouraging and inspiring feedback on my work and for your very constructive and helpful comments that have definitely improved the paper a great deal. I had studied all of your comments very carefully and re-organized my manuscript. According to your comment, the mistake of “keywords” is corrected, and the novel contribution is added in section 5( Discussion And Implication) as the theoretical and practical contributions. In this revision, grammatical and writing style errors in the original version have been refined and edited by my friend who is a native English speaker.

The relevant contents are as follows:

5.2 Theoretical contributions

This study is a pioneer to examine how different dimensions of CI generate direct effects on innovation in service firms. While many previous studies often link customer CI, supplier CI to service innovation[ ],[ ],[ ] without taking opponent CI into consideration, this study has proposed effects of opponent CI on exploratory and exploitative service innovation. Our empirical testing has found the effect of opponent CI to be strongly supported, with the two paths significant in the hypothesized directions. As a result, this contributes to the development of a more comprehensive account of opponents’ behavior.

Response to Reviewer 3’s Comments

First of all, thank you very much for your very encouraging and inspiring feedback on my work and for your very constructive and helpful comments that have definitely improved the paper a great deal. I had studied all of your comments very carefully and tried to incorporate all of them into the current version of the paper. Please find more detailed descriptions of how I did that below. I have modified our paper to accommodate your concerns (major changes in the article are written as notes in the margin on each page for your quick perusal). In addition, I provided a point-by-point response to each of your comment. For ease of distinction, your originals comments are listed below in regular font, and my responses to those comments are shown in italics font.

Reviewer #3: 1. All discussion is too general without any comparison. I suggest authors should compare your results with others’ reports so as to find different conclusion.；

Than you very much for you helpful suggestion. I rewrote this the conclusion section and compare my results with the recent findings. Here are the comparisons in the revised edition:

2. please have the paper thoroughly edited to address some grammatical errors that exist throughout the paper；

Thanks deeply for your suggestion. We have refined the sections of literature review, research method, data analysis and discussion. Furthermore, in this revision, grammatical and writing style errors in the original version have been refined and edited by my friend who is a native English speaker.

3. The authors state this approach is first used in this research field, How? There is no evidence in this paragraph.

Thanks a lot for your helpful comment. I rewrote this part with some evidence in this part. The relevant contents are as follows:

This study is a pioneer to examine how different dimensions of CI generate direct effects on innovation in service firms. While many previous studies often link customer CI, supplier CI to service innovation[ ],[ ],[ ] without taking opponent CI into consideration, this study has proposed effects of opponent CI on exploratory and exploitative service innovation. Our empirical testing has found the effect of opponent CI to be strongly supported, with the two paths significant in the hypothesized directions. As a result, this contributes to the development of a more comprehensive account of opponents’ behavior.

4. Where is the discussion of this literature? This is important.

Thank you very much for your insightful suggestion. I rewrote the discussion section which now consists of 5.1 Conclusions, 5.2 Theoretical contributions, 5.3 Practical contributions, 5.4 Limitations and future research. The relevant contents are as follows:

5. Discussion And Implication

5.1 Conclusions

5.2 Theoretical contributions

This study is a pioneer to examine how different dimensions of CI generate direct effects on innovation in service firms. While many previous studies often link customer CI, supplier CI to service innovation[ ],[ ],[ ] without taking opponent CI into consideration, this study has proposed effects of opponent CI on exploratory and exploitative service innovation. Our empirical testing has found the effect of opponent CI to be strongly supported, with the two paths significant in the hypothesized directions. As a result, this contributes to the development of a more comprehensive account of opponents’ behavior.

5.3 Practical contributions

5.4 Limitations and future research

Firstly, this study got data mainly from tourism enterprises, such as tourist attractions, hotels, food and crafts companies, travel agencies and so on. This study considers tourism enterprise as typical service businesses, therefore, it does not consider the different features of sub-types of service enterprises. Secondly, this study is conducted in east China, which has a unique cultural and economic environment in China. The generalizability of our findings to China’s service enterprises will need to be confirmed with additional studies in different places to take account of the differences in culture and economy. In the future, further researches about service innovations of different types of service enterprises in different places are need.

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PLoS One. doi: 10.1371/journal.pone.0236412.r003

Decision Letter 1

Bing Xue

8 Jul 2020

Competitive Intelligence and Its impact on Innovations in Tourism Industry of China: An Empirical Research

PONE-D-20-03099R1

Dear Dr. Bao,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: The manuscript has been refined as per comments given. The authors show that opponent CI

and supplier CI have positive influence on both exploratory and exploitative service innovation. This is fine, I recommend that the paper be accepted and take following measure before:

1. Can authors just address other methods, maybe statistical to tackle the problem (for the sake of future direction)

2. Limitations of research is very important to mention.

3. Again authors have started subsection immediately after section without any content in section, this has to be avoided.

4. Equations to be written properly using equation editor.

5. Improve the language of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0236412.r004

Acceptance letter

Bing Xue

14 Jul 2020

PONE-D-20-03099R1

Competitive Intelligence and Its impact on Innovations in Tourism Industry of China: An Empirical Research

Dear Dr. Bao:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Professor Bing Xue

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Data. English and Chinese quesitonnarie.

(DOCX)

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S2 Data. Ethical statement.

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S3 Data. CI&SI(confimatory and amos-212).

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S4 Data. CI&SI(exploratory-121).

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Data Availability Statement

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Competitive intelligence and its impact on innovations in tourism industry of China: An empirical research

Yanli Bao

Roles

Abstract

1 Introduction

2 Theoretical background

2.1 Competitive intelligence

2.2 Service innovation

2.3 CI and service innovation

2.3.1 Effect of customer CI on service innovation

2.3.2 Effect of Opponent CI on service innovation

2.3.3 Effect of supplier CI on service innovation

3. Methodology

3.1. Ethics statement

3.2. Data collections

3.3. Measures

4. Data analysis

4.1 Instrument validation

Table 1. Component matrix after rotation of enterprise CI (N = 121).

Table 2. Component matrix after rotation of service innovation (N = 121).

Table 3. Reliability test of CI and service innovation (N = 212).

Table 4. Measurement model fitting results of enterprise competitive intelligence (N = 212).

Table 5. Measurement model fitting results of service innovation (N = 212).

4.2 Assessing the hypotheses

Table 6. Non-standardized regression coefficient.

5. Discussion and implication

5.1 Conclusions

5.2 Theoretical contributions

5.3 Practical contributions

5.4 Limitations and future research

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Bing Xue

Roles

Author response to Decision Letter 0

Decision Letter 1

Bing Xue

Roles

Acceptance letter

Bing Xue

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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