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Table 6 summarises the multivariate analysis results. All variables (WQ1 to WQ 17) under the situational factor "While in the queue' are statistically significant (p = 0.000). Moreover, these factors have a significant influence on emotiona

Table 6 summarises the multivariate analysis results. All variables (WQ1 to WQ 17) under the situational factor "While in the queue' are statistically significant (p = 0.000). Moreover, these factors have a significant influence on emotiona

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2. Literature Review walling were undertaken pregdomimantty in only taree nations, 1.€., Ne UK, UsA, and Canada. Prior studies on waiting argued that cultural explications of time, waiting delays, and customers’ waiting behaviour differ substantially [10, 11]. The fast pace of today's life has left most shoppers with little tolerance for waiting, particularly while shopping. Pressure on people's time is higher than ever in India with the rise in dual-earner couples, longer working hours and the need for social connectedness. Previous studies have advocated customer emotions during unpleasant shopping confrontations. However, it paid less attention to customers waiting at the retail checkout in a developing country like India. This study examines the implications of waiting in the queue at the checkout, the associated emotional discomfort, and the customers' behavioural intentions.
2. Literature Review walling were undertaken pregdomimantty in only taree nations, 1.€., Ne UK, UsA, and Canada. Prior studies on waiting argued that cultural explications of time, waiting delays, and customers’ waiting behaviour differ substantially [10, 11]. The fast pace of today's life has left most shoppers with little tolerance for waiting, particularly while shopping. Pressure on people's time is higher than ever in India with the rise in dual-earner couples, longer working hours and the need for social connectedness. Previous studies have advocated customer emotions during unpleasant shopping confrontations. However, it paid less attention to customers waiting at the retail checkout in a developing country like India. This study examines the implications of waiting in the queue at the checkout, the associated emotional discomfort, and the customers' behavioural intentions.
Sample demographics. Table | gives the sample description. Among the respondents, 41.6% were in the 31-40 age bracket, and 8.1% were older than 50 years. To obtain a broader insight into the issue under study, responses were gathered from both genders (male and female). Therefore, there is no significant variation in opinion share among both male (53.8%) and female (46.2%) respondents. The nearly identical composition of both formats (49.4% and 50.6%) has ensured accessing sizeable,
Sample demographics. Table | gives the sample description. Among the respondents, 41.6% were in the 31-40 age bracket, and 8.1% were older than 50 years. To obtain a broader insight into the issue under study, responses were gathered from both genders (male and female). Therefore, there is no significant variation in opinion share among both male (53.8%) and female (46.2%) respondents. The nearly identical composition of both formats (49.4% and 50.6%) has ensured accessing sizeable,
Regression analysis of emotional discomfort while in the queue. Note: Significant at: *0.05, ** 0.01 levels. Table 2.
Regression analysis of emotional discomfort while in the queue. Note: Significant at: *0.05, ** 0.01 levels. Table 2.
Correlations between impulse buying behaviour while in the queue and discomfort experienced. The respondent's action of spontaneous purchase is significantly negatively correlated with the "discomfort while in the queue" (where r = -0.180, p = 0.000). It suggests that customers make fewer impulse purchases when their discomfort level is high. The respondents spend more money than planned when the range of products at the checkout is pleasing. This action is significantly negatively correlated with the "discomfort while in the queue" (where r = -0.144, p = 0.005). It indicates that customers spend less on impulse buying when their discomfort level is high. The instances of "respondent regretting about making a wrong choice in a hurry" are significantly negatively correlated with the "discomfort while in the queue" (where r = -0.327, p = 0.000). It suggests that customers worry less about a hurried decision to buy a product when their discomfort is high. Fa ee ee, ee a a ee ee ee ee, ee ee a ee . ee ae, a a ee: ee 4.2. Correlations Between Impulse Buying Behaviour While in the Queue and Discomfort Experienced Respondents visiting the retail outlets browse merchandise displayed at the checkout and make impulse buying decisions. Table 4 presents the correlations between impulse buying behaviour while in the queue and the discomfort experienced by the respondents.
Correlations between impulse buying behaviour while in the queue and discomfort experienced. The respondent's action of spontaneous purchase is significantly negatively correlated with the "discomfort while in the queue" (where r = -0.180, p = 0.000). It suggests that customers make fewer impulse purchases when their discomfort level is high. The respondents spend more money than planned when the range of products at the checkout is pleasing. This action is significantly negatively correlated with the "discomfort while in the queue" (where r = -0.144, p = 0.005). It indicates that customers spend less on impulse buying when their discomfort level is high. The instances of "respondent regretting about making a wrong choice in a hurry" are significantly negatively correlated with the "discomfort while in the queue" (where r = -0.327, p = 0.000). It suggests that customers worry less about a hurried decision to buy a product when their discomfort is high. Fa ee ee, ee a a ee ee ee ee, ee ee a ee . ee ae, a a ee: ee 4.2. Correlations Between Impulse Buying Behaviour While in the Queue and Discomfort Experienced Respondents visiting the retail outlets browse merchandise displayed at the checkout and make impulse buying decisions. Table 4 presents the correlations between impulse buying behaviour while in the queue and the discomfort experienced by the respondents.
Table 5. Relationship between customer engagement and discomfort in the queue. Therefore, browsing behaviour is independent of discomfort levels while in the queue. The respondent's behaviour "glancing through mobile phone" correlates negatively with the "discomfort while in the queue" (where r = -0.126, p = 0.013) and is significant. So, as the respondent spends more time looking at their mobile phone, their discomfort decreases. The respondent's behaviour of "engaging in conversations" correlates negatively with the "discomfort while in the queue" (where r = -0.162, p = 0.001) and is significant. So, as the respondent spends more time chatting with their family members or friends, their discomfort decreases. Further, the overall customer engagement correlates negatively with the "discomfort while in the queue" (where r = -0.119, p = 0.02) and is significant. It implies that as customer engagement increases, their discomfort reduces.
Table 5. Relationship between customer engagement and discomfort in the queue. Therefore, browsing behaviour is independent of discomfort levels while in the queue. The respondent's behaviour "glancing through mobile phone" correlates negatively with the "discomfort while in the queue" (where r = -0.126, p = 0.013) and is significant. So, as the respondent spends more time looking at their mobile phone, their discomfort decreases. The respondent's behaviour of "engaging in conversations" correlates negatively with the "discomfort while in the queue" (where r = -0.162, p = 0.001) and is significant. So, as the respondent spends more time chatting with their family members or friends, their discomfort decreases. Further, the overall customer engagement correlates negatively with the "discomfort while in the queue" (where r = -0.119, p = 0.02) and is significant. It implies that as customer engagement increases, their discomfort reduces.
cL > Se eae The empirically validated model with path coefficients.
cL > Se eae The empirically validated model with path coefficients.
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Situational Ethics
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