Keywords

Customer Service, Customer Complaint, Complaint Intention, Loyalty, Repurchase, Online Retail, Purchase, Complaint Behavior, Attitude, Service Failure.

Introduction

The global online retail market is projected to expand at a considerable pace. In 2019, online retail sales amounted to USD 3.53 trillion and is projected to grow to USD 6.54 trillion by 2022. Online shopping has become one of the highly trendy online activities Clement(2020).

Like all businesses, the online business also has its fair share of challenges; for instance, finding the right product assortment that is more appealing to customers Caruana & Ewing (2010), generating traffic towards the website, nurturing both the present and new customers on the platform Pitta, et al. (2006) conversion rates and retention of the existing customers Nemzow, (1999) using the right technology, and most importantly be profitable in the long run.

There is an increasing organizational importance with regards to consumer satisfaction as a method for assessing service levels. Enhanced consumer satisfaction assessments are extensively believed to be the finest indicator of an organizations potential revenues. Higher Customer satisfaction and loyalty impacts the cost incurred on promoting the brand as there is lesser revenue spent on retaining existing customer rather than convincing newer ones Bendle, et al. (2019). Study done in this area clearly indicates that increase in retention will lead to enhances profitability which in turn further enhancing the chances for further sale Reichheld(2014). Customer loyalty substantially effects a company’s success. Customer satisfaction impacts customer loyalty, and perceived recovery quality which in turn affects satisfaction DeTienne & Westwood (2019. Customer satisfaction influences distinct aspects of an organization’s financial performance which aspect when ignored impacts the firm’s forthcoming cost of selling. Lim, et al. (2020)

Nevertheless, knowing what a customer is unhappy about their purchase can be tricky and challenging, as many customers choose to exit the service when they experience a substandard service. Alternatively, others may be vocal in their criticisms, thereby prompting ‘negative’ word-of-mouth through reviews and feedbacks. Thus, it is difficult for a firm to exactly quantify unsatisfied customers. Hirshman(1970) Singh & Wilkes(1996 Many organizations, on the other hand, do not give adequate attention towards managing customer complaints successfully. This is astonishing, as consumer grievances are a prized resource to gather marketplace information, which organizations should use to recognize and evaluate the core trigger for customer dissatisfaction.

Customers’ complaining behaviour can be interpreted as a set of potential customer reactions to unsatisfactory buying encounters. The common customer complaint behaviour includes seeking redress, engaging in negative word of mouth, or even exiting. If a firm handles these three options both effectively and efficiently, the likelihood of complaint would consequentially reduce, and the repurchase and loyalty intention would increase manifold. Customer delight leads to repurchase intentions which in turn enhances customer understandings of exceptional service and provides organizations with a chance for substantial profits (Meyera, et al (2017)

Existing literature has dealt substantially with the topic of ‘customer’s intention to complain’ across various service industries. Scales have been developed to measure this aspect, though specific to the airlines Alotaibi (2015) and the tourism industries Kim (2009) and brand equity Yoo & Donthu (2001) to name a few. Another set of researchers have explored the need for effective handling of complaints that has an important managerial connotation for re-purchase intention, which in turn leads to higher profitability Landon. E (1977) Jacoby & Jacarrd (1981) Hoffman, et al (1995) Hart, et al (1990), and promoting complaining behaviour Fornell & Larcker (1981) Ndubisi & Ling (2006)The literature on intention to complaint have looked at numerous contributing factor of customer complaint behaviour comprising of cost Richins, (1980)attitude (Bearden & Mason(1984) Singh & Wilkes (1996)knowledge and controllability Day (1984) Folkes (1984)the likelihood of successful complaint Granbois, et al., (1977) and environmental and demographic variables (Singh & Wilkes, 1996). Online purchase platform as an interactive channel provides the consumer an instant and easily comprehensible path to broadcast their sentiments and opinions about the purchase Dellarocas (2003). Specifically, disgruntled consumers will vent their adverse encounters with regards the items they bought, they can criticize using the web at exceedingly minimal expense, remoteness and expenses does not have an impact on the complaining behaviour which is the case when it comes to traditional retail.

Complaining online reduces the psychosomatic expenses Zaugg, (2006) and extends may be a guarantee of an immediate and instantaneous response. Cho, et al (2002) mentions about the reaction being crucial to e-commerce shoppers than to those who buy from the brick-and-mortar stores. Putting a complaint on a social media platform is intended not merely at expressing one’s grievance to the target company – it is not only like a ‘public’ retort it also ends up propagating the information to a larger consumer base online. Online shoppers complaining about online manners show that 39% published a criticism on the organization’s internet site, 16% on gradings done on sites and 7% on a web log. There is a difference in the way a consumer reacts to discontentment when it comes to the Online shopping environment as it does not provide direct interaction between the customers and sellers. As per Alba, et al (1994) one on one contacts can enhance consumers' trust and post-buying contentment because some merchandise features are additionally clearly noted with the touch and feel before the actual buying happening. The absence of face-to-face contacts coupled with the disillusionment which happens occasionally when the merchandise reaches the consumers could lead to a rise in the inclination to grumble more in the e-commerce purchase sphere.

Research has indicated that e-commerce buyers vary when compared to the conventional retail buyers in numerous characteristics throughout the purchase progression, e-commerce buyers thought process is not just about the merchandise quality and value but also perils involved with e-commerce purchases, such as safety and confidentiality of the data, and the purchase platform’s look and feel Shankar, et al (2003)The purchase platform in the e-commerce environment should be seen by the buyer as trustworthy, reliable and also user-friendly. Personalization, Assurance, Responsiveness, Reliability, Information Quality, Website Usability becomes important cues when it comes to customer purchase and posts purchase interactions.

Therefore, a similar, e-service quality measurement instruments may run into to a misleading conclusion. The Scale development Instrument must contemplate the elements of the e-service distribution structures. Wolfinbarger & Gilly (2003) clarify questions found in e-commerce quality composition as there are little commonality which exists even among the scales developed for measuring website characteristics to consumers and intention to complain. E-commerce excellence with regards to the website is about giving the customer an effective buying experience Zeithaml (2000). Eventually, with the help of this scale, both researchers and managers would be empowered to better comprehend the ‘intent’ behind consumer complaints. This is important as online retailers need to know that complaints denote a chance to rectify their products or services, and thereby positively impact subsequent customer experiences. Further, if one understands the attributes, which go on to develop the intention to complain; this, would give a marketer the much-needed perspective to understand the rationale of the complaining behaviour.

Literature Review

Consumer complaint behavior can be well-defined as a procedure which “constitutes a subset of all possible responses to perceived dissatisfaction around a purchase episode during consumption or possession of the goods or services” Crie (2003) If we look at things from a consumer experience execution point of view, it is critical to contemplate a universal point of view that clearly incorporates the emotive nature of consumer reaction Kranzbühler, et al (2018). Current study similarly emphasizes on the weightage to be given on emotional rejoinders about elements that propel buyer engagement Hollebeek, et al. (2019)

It is a substantial source of information for the organization to judge the product quality, the price, and the Brand itself. This set of information offers not only an opportunity to the retailers to bring corrective changes to their products and services which could not only satisfy in a better way but also will have a positive impact on the consumer’s behaviour subsequently Blodgett, et al(1977) Consumer complaint can also be defined as “expression of dissatisfaction on a consumer’s behalf to a responsible party” Landon. E (1977) On the other hand, Jacoby & Jacarrd (1981) defines a consumer complaint as “an action taken by an individual which involves communicating something negative regarding a product or service to either the firm manufacturing or marketing the product or services or to a third-party entity”. Consumer deflecting from a specific brand could lead to larger consumer turnover which in turn would be an added cost for the organization as it would be costly to lure a fresh consumer than to retain the current one Hart, et al (1990) Buyer grievances offers a chance for upgrading processes, boosting consumer relations, and enhancing shopper allegiance which in turn improves profitability. To accomplish the same, attending to buyers and overseeing their obligations and criticisms is imperative Yu-Hsiang, et al (2016). Customer grievance revival is only a fraction of many customer retentions instruments. Customer allegiance inventiveness which when scrutinized through the lens of a CLV model, comes at a price which could impact the effectiveness and revenue targeted and generated from that consumer base, developments in the areas AL-ML can simplify the handling of numerous characteristics of CRM in a way that will not hamper revenues Morgeson, et al (2020)

Given the high possibility and the easiness with which a consumer may exit the association and may shift to a different service provider with just a click of a mouse, maintaining service levels is paramount as ever in this sphere Holloway. & Sharon (2003).

Companies are yet to give enough importance to handling consumer’s properly whenever they have an issue with the services or product, consumers are not handled effectively Homburg & Furst (2005)Retailers who receive few complaints tend to believe that the consumer is generally satisfied with its product and services and hence would be loyal Johnston (2001) Blodgett & Haitao (2007) Fornell & Wernerfeldt.B (1987)There is substantial evidence that consumers once satisfied with their grievances become more loyal and hence more money accrues to the organization due to re-purchase Blodgett & Haitao (2007)Researchers mention that it is not the service failure but the organization's response to the service failure that triggers dissatisfaction Hoffman, et al. (1995).

Consumer exit or change of loyalty for a particular brand impacts the long-term revenue generated by the organization (Andreassen (1999) According to (Hirshman (1970) and Fornell & Wernerfeldt.B (1987), the number of Consumers who exit the buyer-seller relationship can be reduced. If a retailer is receiving fewer complaints, it may be just because rather than complaining about a deficiency in the product or service the consumer is just switching to the competition. Stephens & Gwinner (1998). The customers involvement with the brand is a vital tactical instrument to develop long term preference, thus shaping the mindset towards actual repeat buying habits Reham, et al (2016). Consumer switching behaviour Homburg & Furst (2005) and the spread of negative word of mouth Phau & Baird (2008) both inevitably lead to an increase in cost for the company because it is always more expensive to attain new consumers rather than retaining the existing one. Customer switching behaviour will also depend on procedural switching cost (Time, energy, risk, money), financial switching cost (Loss of brand loyalty benefits) and relational switching costs (affiliation with the brand which is both emotional and psychosomatic) Burnham, et al (2003)A level of knowledge the customer has about the market also plays a significant role when it comes to their swapping decision Carmen, et al (2007), in today’s world where social media plays a critical role in developing perception, an unfair negative review can reduce positive consumer responses to a firm Allard, et al (2020).

Researchers suggest that organizations should promote complaining behaviour among their consumers Fornell & Wernerfeldt.B (1987).A public complaint (complain made directly to the company) made by the consumer gives the company a chance to address the same and make amends by appropriately compensating him or her and thus improving retention Ndubisi & Ling (2006)on the other hand private complaining (complaints made to other Consumers, family members, friends or peer groups) does not give the company a chance to rectify the wrong which in turn reduces the consumer base Bearden & Oliver (1985).

Hence an understanding of the customer's reluctance to complain or why customers behave in the way they do is important to understand the factors which influence the intention to complain. This knowledge with facilitate better policies and involving retention strategies. Service failures cannot be ruled out, but it is possible to curtail the influence with tactically scheming service recovery processes and systems which will thus decrease the outcome of negative emotions among the consumer Svari, et al (2011).

Study Hirshman (1970) show that consumer makes a rational judgment regarding the complaint merit on the lines of product/service dissatisfaction, the profitability of success (of complaining), the resolve taken to express one’s dissatisfaction and the cost of that merchandise. The perceived likelihood to get redress for the complaint lodged is identified as a crucial element of grievance expression Blodgett & Anderson (2000).

The role played by personality traits in predicting the complaining behaviour of a consumer-first came to the fore in the 1980s Bearden & Mason (1984) Moyer (1984) Richins (1980) found that extraversion and complaint propensity was positively related. In the research, the author mentioned that nonassertive individuals appear to be more anxious to voice their complaint regarding an unsatisfactory experience. There was a positive relationship between assertiveness and complaining behaviour.

Negative emotions like disgruntlement, frustration or discontent are major rationales behind the promptness of the complaining behaviour among the consumers as according to Giese & Cote, (2000). Each assessment among the consumer is inclined by a fixed set of sentiments and consequently affects one’s intention to complain. Emotional Consumer conduct can also be an amalgamation of antagonism, frustration, sadness, and numerous another undesirable emotional state which in union causes unfavorable reaction towards the service provider Dallimore, et al (2007).

If the consumer has gone through a prior service discontentment they learn from their past experience, so previous positive experiences will create a positive attitude towards complaining Singh & Wilkes (1996). The spread of the previous complaining familiarity can strengthen an individual’s mindset and behavioural temperaments in forthcoming circumstances, Singh & Wilkes (1996) to add to it shoppers who have gone through a previous complaints experience might build up a perception as to in what manner an organization may perhaps respond to the voiced complaints and the linked cost and remunerations involved in it, Kim, (2009). Customer attributes added importance to preceding positive brand encounters than to freshly amassed intelligence as according to study done by Krautz & Hoffmann (2017).

The principal element that fosters the choosing to pursue or not to pursue compensation is the apparent probability of success Day & Landon (1976)Probability of success implies the consumer’s assessment of the retailer’s commitment to resolve the service crisis minus the difficulty Richins (1983)In the model proposed by (Blodgett, et al.(1993) regarding complaining behaviour for the dissatisfied consumer who sought a redress they mention four factors, Stability/Controllability, Attitude towards complaining, Probability of accomplishment with regards to the grievance made along with the importance the product hold in the consumers thought process. Companies underestimate the importance of customer perceptions of quality in driving satisfaction, customers’ loyalty, and complaint behaviour Tomas, et al (2017 )

Reimbursements from complaining is a vital variable since it supports an explanation as to why numerous consumers do not protest once they are discontented and why certain people have a habit of complaining. Studies also indicate that customer reaction to service failure can also be linked to demographic variables like age education income. Day, (1984) Jacoby & Jacarrd, (1981). Age is repeatedly used to predict complaining behaviour however its impact is often unnoticeable, Bearden, et al (1979) found that age adversely conveys to complaint behaviour in the automobile industry, in a more common context age has demonstrated to positively correlate with public complaints. Older consumers are predictable for publicly complain more than the younger ones as they have amassed more information and understanding in dealing with the complaint or service failure scenarios Kim, et al (2003) Kolodinsky (1993) Elderly customers habitually pursue data from private sources like word of mouth while determining which store to support or what product to purchase Lumpkin & Barnett (1982).

Though individual qualities and demographics could hold the foremost cues to categorize factors that may impact intention to complain, there are other features which may not be directly associated but will surely impact, this could be the Brand itself, the Company policies, peer influence, type of consumption, product, cost incurred on the product.

With regards to involvement in the purchase or to be specific the type of consumption as to for whom the product was purchased would have a bearing on the intention to complain, extra involved a shopper is with the purchase or a consumption state, the chances of the individual to utilize their resources which includes the financial loss or gain, the energy and time involved to make grievance Lau & Ng (2009). As an antithesis, with regards to less engaging circumstances, consumers are not likely to be concerned considerably regarding a unsatisfying experience with their purchase. Chebat, et al (2005) highly involved customers tend to show a higher level of satisfaction or dissatisfaction Pritchard, et al. (1999) Marketers must develop an in-depth understanding of consumers’ lifestyle preferences, choices, and aspirations, especially the younger generations Tamana, et al (2019).

The perception the individual carry about the brand also has a bearing on the intention to complain, repute the retailer carries for approachability Richins & Verhage (1985) plus an individual's positive evaluation of an organization leads to commitment Tax, et al (1998). While evaluating a brand’s ability to handle service as per research an individual looks at a brand from three perspectives one stability, would the dissatisfaction with the product happen multiple times, second is service providers control over the problem (was it avoidable), and locus (is the accountability on the buyer or the provider Hocutt, et al (1997). Another facet of the brand which holds importance about the complaint behaviour is Company policies regarding redressals, apparent impartiality of the compensation presented by the service giver (If the consumer is extended an exchange, financial compensation). When there is an unsatisfactory service encounter, the buyer expects a compensation for any loss incurred due to that purchase. The value of the compensation depends on the severity of dissatisfaction because of the purchase Hocutt, et al (1997), an alternative facet of interactional equality, is an expression of regret, this also appears very appropriate with regards to grievance settlement Goodwin & Ross (1992)With regards to cost both the cost involved in complaining and the price of the product has a bearing on customers` complaint tendency, so the price level of that product/service and cost of making a complaint is both relevant Richins (1980). The benefit for the consumer with regard to a complaint is the outcome or end result not including the expense incurred for the complaint. This consequence is the outcome projected with regards to the impact and kind of cost experienced Landon. E (1977) With regards to product, the structure of the market, alternatives available, and the complexity of the product would also impact intention to complain Crie (2003).

Methods

Distinct ranges of buyer data were analyzed throughout the various stages of the scale development. Eighteen persons were a section of the focus group meetings. The number of persons per focus group session is acknowledged as mentioned in the study by Krueger, (1988) The individuals were selected based on their activities regarding Online Retail and based on the purchase patterns they mentioned Nine Marketing Professors from the areas of Marketing, Consumer behaviour, Retail and Operations research teamed up in the Scale validation process. The experts were invited for the same keeping in mind their knowledge in the fields associated with the idea of the scale which was intended to be developed. Direct consultations were employed in complete pretest and validation process. The people who were part of the interview were contacted in a non-systematic way for this survey. Besides giving the required training for being a part of the survey they also got a handbook with data gathering process guidelines. For the purification step, one survey consisting of 437 respondents were carried Hair, et al (2010) Pett, et al (2003) in their study mentioned that for factor analysis the benchmark to followed is to have 5-15 respondents per item.

Scale Development

Traditional measures suggested by Gilbert & Churchill (1979) and De Vellis (2003) were pursued to build on the Consumer Intention to Complain scale and remain explained underneath.

Step 1 Construct Specification

In the current study, the Consumer Intention to Complain was measured keeping multiple factors in mind and the components are detailed employing literature as mentioned in the previous segment. The Consumer Intention to Complain facets were identified as Consumer-centric, Retailer centric and Demographic.

Step 2 Item Writing

A bunch of factors and associated components with the Consumer Intention to complain as mentioned in step 1 was listed by way of literature and two focus group assessments. The overall purpose of these studies was to categorize the different facets of Consumer Intention to complain during the consumer decision-making process concerning complaining behaviour. To list down the items, the suggestions stated by De Vellis, (2003) were ensued and three to five items were established for each aspect of Consumer Intention to complain.

Step 3 Content Validity

A panel of 10 PhD students and two marketing Professors were requested to contribute to a survey to evaluate the content validity of the items created after the preliminary stage. All panelists were given the customary course with the meanings of the factors and items mentioned and the scheduled proportions. Further, all participants were part of the one-to-one discussion to avoid any probable misunderstanding with regards to the research. The selected items and the connected section of the study were identified to the scholars. Being in line with the process suggested by Anderson J. Gerbing (1991) The two keys, ‘the proportion of substantive agreement’ and ‘substantive-validity coefficient’ were also taken up as suggested by Anderson J. Gerbing (1991) as a preliminary measure by which to forecast the performing items while doing the CFA.

Step 4 Pre-Test

Post validation of the substance, the evaluation mechanism (consisting of the Consumer intention to complain scale and the socio-demographic items of the shopper, such as gender, age, family income, educational level) was then put through the initial test with fifty consumers. The objective of this phase was to assess the completeness and accuracy of the elements in the questionnaire and answer given and the time taken for submitting the options. A check was kept if they felt that the questions or reply with the choices given were easy or not to comprehend.

Step 5 Scale Purifcation

The purpose of this phase was to understand and shortlist factors that were pertinent for being representative of the construct, that is, Consumer Intention to complain and its aspects, removing items that created inaccuracies which could hamper the model fit (Gilbert & Churchill (1979). The relevant statistical norms with regards to the item analysis the consistency and EFA were carried out. Decisions were taken with regards to a particular item to be removed or retained to increase the consistency of the proposed scale. Hair, et al (2010) study was benchmarked to ensure that the Cronbach alpha is as per permitted research standards.

The appropriateness of the study was verifies using exploratory factor analysis, Bartlett’s test of sphericity, KMO test and the Measure of Sampling Adequacy –MSA as cited by Hair, et al (2010) Pett, et al (2003). Two benchmarks were employed to map the number of factors: the latent root criterion (eigenvalue > 1) and the screen test. Hair, et al (2010) Pett, et al (2003) suggested a loading between 0.3-0.4. In the current study, value preferred was 0.5 as followed in studies done prior Forsythe, et al (2006). Further, as mentioned Pett, et al (2003), a high factor loading (P0.5) on various factors (high cross-loadings) must be omitted or keeping in mind their academic significance the same be earmarked jointly with the factor where they look the most adaptable. The Cronbach’s alpha coefficient for all the items were assessed.

Step 6. Construct validation

The intent of this action was to assert and certify the configuration of the items on Consumer Intention to complain scale. The data gathered in the (n=437) was evaluated. Maximum likelihood method was used to get the rightly assessed model, examining the covariance matrix, using SPSS and SPSS Amos, for structural equation modelling. The model fit was evaluated as per the cutoff principles as stated in the study by Hair, et al (2010). The measures stated by mentioned researchers were also tracked to estimate the convergent and discriminant validities. The purpose of this segment was to explore convergent validity to gauge the extent to which two items of the matching factor are linked. As per the recommendation by Hair, et al (2010) Fornell & Larcker (1981) the present study employed specific tenets to review the convergent validity of the preliminary seven-factor, 19-item ‘consumer intention to complain’ scale. Main attention was given on standardized loading being 0.5 or higher and preferably 0.7 or more, Average Variance to be more than 0.5 and Construct Validity being higher than 0.7.

Results and Discussion

Study Population

Table 1 shows the Socio-Demographic attributes of the populace surveyed. There was an effort to get respondents from all age group and with a varied monthly income and from across geography, there were respondents from 72 cities.

Table- 1 Socio- Demographic Characteristics
	Focus Group-10	Pre-test-49	Purification-443
Gender
Male	7	31	255
Female	5	18	188
Age
18-24		17	175
25-34	4	8	137
35-44	3	12	68
45-54	4	5	57
55-64	1	7
65 plus
Monthly Income
20000-30000	3	13	171
30000-40000	7	12	73
40000-50000			95
50000-60000		12	33
60000-70000		8	13
70000+	2	4	52
Educational Level
Under Graduation		13	23
Graduate			174
Post-Graduation	10	27	232
Doctorate	2	9	8

Scale Development

Step 1 and 2 construct specification and item writing

The outcomes gained from the focus group indicated that the contributors were concerned about the lack of a procedure when it comes to the systems and processes regarding the Consumer complaint process. The participants were more frequently talking about the “Difficulty in the Complaint process, regarding money transfer, poor back-end services, the whole process running very slow. Others talked about the brand and the company policies if they are robust that would encourage them to complain. Some participants were mentioning the loss which they have incurred if that justified the money and time, they would spend on the complaint process. Others talked about peer influence and the whole purpose of the purchase influencing their intention to complain.

Step 3 Content Validation

The measures were calculated, which lead to four measures with Csv < 0.5 being omitted. The measures that did not convene to the accepted assessment and could lead to misperception concerning the measurement the item best defines. 10 items meet required levels, and their values were more than 0.5, which verifies that these items were largely allocated to the meant construct. Then, items with lesser value were amended keeping the panel’s recommendations in mind. The remaining items, almost all specialists accurately named to the intended factor, were retained for taking the study forward.

Step 4 Pre-Test

The Questionnaire formats which the respondents noticed were problematic to comprehend in the pre-test assessment were reviewed. There were headings in the 7-point scale which seemed similar, and differentiation was getting difficult. The same was reworded.

Step 5- Scale Purification

The scrutiny of the data set amassed from the respondents was the first criteria, the records of (n-437) surveys showed an overall Cronbach alpha of 0.797 implying good internal consistency. The values for item-total correlation varied from 0.486-0.786 which was deemed acceptable as per prior research. The pertinent technique was followed while doing the EFA. The suitability of the data and the sample size was checked using the KMO test and Bartlett’s test of sphericity. Conferring with Hair, et al (2010) which mentions about having at least five times as many observations as the number of variables to be analyzed. Hence, having 437 responses for 69 items was considered well-thought-out and acceptable to analyze the data using EFA. The outcome stated a KMO figure of 0.732 for the complete dataset. Prior studies asserts that the sample is acceptable or adequate if the estimate of KMO is higher than 0.5 Field, (2000), as per Pallant (2013) the acceptable value of KMO is 0.6 or higher. Kaiser, (1974) validates that the lowest acceptable point is of 0.5 and the figure which falls between 0.5 and 0.7 is considered average, figure between 0.7 and 0.8 is good, and anything above 0.8 and 0.9 is considered as excellent (Hutcheson & Sofroniou (1999) The current study with a KMO reading of .732 as per literature is having a “Good” value for taking the research forward.

SPSS 22.0 tool was employed to execute the principal component analysis with Promax rotation on the 69 items. Eigenvalues, scree test plot and variance have being employed to generate extracted items. As per study done by Cattell (1966) the scree in the scree plot at seven factors was noted as the recommended Seven-factor model of ‘Consumer Intention to Complain” in the current research. This research kept a minimum factor loading of 0.50 as the least possible cut-off as recommended by Hair, et al (2010). Founded on this evaluation, fifty items were eliminated employing an iterative procedure. All the retained 19 items was loaded onto its proposed factor. The scree plot solution showing a 7-factor model was chosen as it was showing the variance explained as 78.22. The examination of the factors carried out with the 19 items which accounted for 78.22 variance and had the Individual Bottleneck which had 3 items having Cronbach alpha of 0.812, The product Deficiency factor had 3 items with Cronbach alpha of 0.872, Complaint Handling with 4 items with Cronbach alpha of 0.848, Company policy with 3 items having a Cronbach alpha reading of 0.831, brand, peer influence and purchase involvement had Cronbach alpha of 0.787,0.867 and 0.853, respectively.

In Table 2 it can be observed that the shopper gave greater mean values to Product deficiency, Company policies, Brand, and Purchase Involvement. In terms of Individual bottlenecks the higher mean was given to the effort which goes to make a complaint, about product deficiency it was as per the literature that the higher the loss incurred higher would be the intent to complain, with regards to the Complaint Handling the consumer felt that the money transfer delay was more important, Company policies and the brand both had high means attached to it which shows that the perception in the Market about the brand and what policies the Brand puts across to the consumer were allotted higher means. Peer influence had a relatively lower mean attached to it but when it came to the Purchase Involvement the intention to complain was higher if the product was purchased for someone special as it had a higher mean allotted by the consumer.

Table- 2 Item-Total Correlation, Factor Structure, Factor Internal Consistency, Cronbach Alpha, Communalities and Mean
Item Analysis		Factor Loading							Communalities	Mean
Item	Correlated Item total Correlation Range	Individual Bottleneck	Product Deficiency	Complaint Handling	Company Policy	Brand	Peer	Purchase Involvement
		Cronbach Alpha   0.812	Cronbach Alpha   0.872	Cronbach Alpha 0.848	Cronbach Alpha 0.831	Cronbach Alpha 0.787	Cronbach Alpha 0.867	Cronbach Alpha     0.863
The time taken to raise a complaint will make me decide whether I want to go through that process or not.	0.662	0.863							0.733	5.05
The money which I would spend in raising a complaint will make me decide whether I want to go through that process or not	0.667	0.822							0.745	5.54
The efforts that I need to take to raise a complaint will make me decide whether I want to go through that process or not	0.655	0.866							0.733	5.56
If I incur a loss of 10%-25% of the amount of money I spend for online purchase I will raise a complain	0.662		0.825						0.712	5.91
If I incur a loss of 25%-50% of the amount of money I spend for online purchase I will raise a complain	0.894		0.961						0.922	6.4
If I incur a loss of more than 50% of the amount of money, I spend for online purchase I will raise a complain	0.703		0.887						0.772	6.57
The follow up process followed by the company is very slow	0.658			0.874					0.687	3.95
Money transfer is late	0.587			0.747					0.567	4.17
The company has a reputation of poor service keeping my past experiences in mind	0.756			0.874					0.772	4.07
The back end services /operator service/call center etc. are poor	0.753			0.855					0.781	4.05
I will raise a complaint if I know that the company has a sure policy on Voice of the Customer	0.671				0.836				0.743	5.78
I will raise a complaint if I know that the company has ‘Service Improvement’ as its priority	0.802				0.928				0.855	5.87
I will raise a complaint if I know that the company revisits its complaint handling procedures regularly	0.617				0.797				0.687	6.03
Will definitely complain because I know the Brand does not take chances with its quality	0.629					0.908			0.822	6.11
Will complain because I know the Brand will surely respond	0.629					0.882			0.818	6.03
Colleagues	0.766						0.945		0.873	5.36
Spouse	0.766						0.928		0.884	4.95
I have purchased the product for another individual and the price is high. I have purchased a high priced	0.759							0.944	0.878	5.93
I have purchased the product for someone special and the price is high	0.759							0.927	0.887	6.2

Of the factors which were evaluated, Individual bottleneck showed the highest percentage of variance (19.48%) which was followed by Product Deficiency (15.58%) and Difficulty in Complain (11.14%). These 3 above-mentioned factors indicated almost half of the total variance (46.47%). (Table 3)

Table- 3 Percentage of Variance Explained and Correlation Between the Factors
Item	% Of Variance explained by the factor
Individual Bottleneck	19.481
Product Deficiency	15.584
Difficulty in Complain	11.143
Company Policies	10.904
Brand	8.188
Peer Influence	7.581
Type of Consumption	5.348

Step 6 Construct Validation

Confirmatory factor analysis was carried out on the 19 item Customer Intention to complain scale, obtaining a model published (Figure 1). The results were as follows the x2/ df= 1.503, RMSEA=0.034, GFI-0.951, CFI=0.983, TLI-0.978 (Table-4) all the values were as per the recommended value of > 0.9 as per the recommendation of (Hair, et al. 2010)

Table 4 Model Fit Indices
Model Fit Indices		GFI	CFI	TLI	RMSEA
Proposed dimensional Model	χ2 (52) = 195.327, p = .000; Normed Chi- Square= 1.503	0.951	0.983	0.978	0.034
Rules of thumb		>.90	>.95	>.95	<0.5
		Good	Great	Great	Good

The standardized factor loadings of the model were significant and had values of at least (0.57) Figure 1. The values of AVE for all the factors were greater than the endorsed value of 0.50, the lowest being 0.708 and with a highest of 0.833. With regards to the discriminant validity, it could see that in all the cases the average variance extracted was greater than the square of the correlations between the factors. (Table 5). All composite reliability ranges were exceeding the advocated point of 0.7, which implies sufficient convergence (ranged from 0.866 to 0.934). About the discriminant validity, it is deducted that the average variance extracted – AVE was higher than the square of the correlation between the factors Table 5.

Table 5 Average Variances Extracted, Composite Reliabilities, Construct Correlations and Square Root of AVE
	Composite Reliability	Average Variance Extracted	1	2	3	4	5	6	7
Individual bottlenecks	0.883	0.716	0.846
Product deficiency	0.922	0.798	0.103	0.893
Complaint Handling	0.934	0.877	0.049	0.107	0.936
Company Policy	0.879	0.708	0.188	0.178	0.11	0.841
Brand	0.866	0.764	0.146	0.458	0.01	0.056	0.874
Peer Influence	0.922	0.856	0.253	0.154	0.155	0.053	0.034	0.925
Purchase Involvement	0.909	0.833	0.145	0.034	0.137	0.232	0.359	0.212	0.913

Discussion

This study’s objective was Item generation and purification of an instrument for measuring Customer Intention to complain, this experimental study has been done on the trial online buyers. The Customer Intention to Complain measurement instrument proposes to find the crucial attributes that build an individual’s intention to complain, which when established may make sure that he/she will not silently withdraw from the brand and would want to vent their dissatisfaction. This enables the organization to retain them, and the service recovery will have an effect on satisfaction. Customer satisfaction impacts customer loyalty which in turn substantially impacts a company’s profitability.

The research examined the major factors that impact CIC as per literature, Hirshman, (1970) in his research cited product/service dissatisfaction, the profitability of success (of complaining), the attempt made to complain and the cost of that merchandise or service. Perceived likelihood to get a compensation was recognized as a critical aspect of complaining behaviour Blodgett & Anderson (2000) Day (1984). Bearden & Mason, (1984) Moyer (1984) Richins (1983) talked about personality characteristics which had an effect on the complaining behaviour Giese & Cote (2000). Lazarus (1991) researched on the emotional reasons for complaining, the attitude related parameters were studies by Singh & Wilkes (1996) Krautz & Hoffmann (2017) Chebat, et al (2005) and others drew up the study with the Brand perspective in mind, how receptive the brand was to the complaint. The Demographic factors were also undertaken in previous studies which consisted of age, income, education, and knowledge level.

The study was initiated with 69 items across multiple factors. The factors which were used to take the research forward were identified based on the eigenvalues, scree test plot and variance. The study used a factor loading of 0.50 as the least possible, fifty elements were eliminated using an iterative procedure. The 19 items which were selected after the EFA were loaded onto its proposed factor. The scree plot solution showing a 7-factor model was chosen as it was showing the variance explained as 78.22. The proposed Seven-factor model Scale to measure ‘Consumer Intention to Complain” in the current research were, Individual Bottleneck, Product Deficiency, Complaint Handling, Company Policies, Brand, Peer and Purchase Involvement.

Several series of validation involving EFA, CFA and reliability analysis endorsed the 7-factor scale. The study demonstrated good psychometric dimensions of the scale. The findings proved Customer Intention to Complain is a measurable construct, evaluation of which is essential for improving customer satisfaction and in a way repurchase behaviour which in turn leads to enhanced profitability as research shows that an upward swing when it comes to retaining consumers by 5% can lead to profitability going up from 25% to almost 95%. Additionally, the success story with regards to percentage of sale to a current consumer is as elevated and the percentage of which lies between 60-70, while to a new customer it ranges from 5-20% Reichheld (2014)

The model can enhances the organizations insight in the area of customer intention to complain to create a stronger relationship marketing framework and to identify the Customer’s approach concerning complaining behaviour. Brands can build policies for boosting the customer's intention to complain and initiate the same so that instead of withdrawing from the brand they are inspired to continue and complain. The study recommends that providing and scrutinizing the quality of information and the brand taking up a sustaining online marketing campaigns can lead to creation of a healthy association amongst the consumers and the online retailer. This is beneficial considering the kind of competition in the market.

Any research conducted will comes with a set of limitations, same is the case with this research too. This study has been formulated on data gathered from participants taken only from India; hence, this study is predominantly India centric owing to which we are incapable to substantiate and/or determine whether our assumptions and connotations would be appropriate to other parts of the globe. Moreover, the study has predominantly focused on online retail (i.e., e-tail); thus, the conclusions may not be relevant for the traditional brick & mortar store retail, particularly since there is a ‘physical interaction’ involved there.

No Scale Development process is complete without the Validation process; a different set of data should be collected and examined to validate the Scale.

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