A Study of Factors influencing buying Behaviour of utilitarian and Hedonic Shoppers: Evidence from FMCG, Sports, Jewelry, Books and apparels retail formats.

 

A. S. Suresh,

Associate Professor, Institute of Management, Christ University, Bengaluru

*Corresponding Author E-mail:

 

ABSTRACT:

In this era where retailers find it difficult to achieve differentiation through the conventional 4Ps of marketing, there is tectonic shift in consumer behavior and expectations where he perceives the shopping experience based on utilitarian or hedonistic traits.  Therefore this research study is undertaken to segment the shoppers on the basis of their traits and their perception about resting areas, in order to understand the influence of resting areas on buying intention of shoppers displaying either utilitarian or hedonistic traits. A survey of 300 retail shoppers drawn from five retail formats Viz (FMCG, Sports, Jewelry, Books and Apparels) and frequency analysis for impact of demographics and Cluster analysis to garner insights about consumer behavior traits was done. One way Anova was used to find out commonalities and differences among different categories of retail stores and impact of resting area. This study revealed that utilitarian and hedonistic consumers behave differently and their perception about resting area is also quite different. Identifying and segmenting consumers on traits enables retail managers to develop the appropriate retailing strategies aligned to retail formats with respect to resting areas to satisfy each segment.

 

KEYWORDS: Retail, Resting Areas, Utilitarian, Hedonistic, Shopping experience, Atmospherics.

 

 

1. INDIAN RETAIL OVERVIEW:

The market for organized retail in the country is growing exponentially despite the downturns. This is because of the economic growth which is pushing more of India’s people into consuming class. By 2017, more than 300 million shoppers are likely to patronize organized retail chains. Another important factor which contributes to growth of retail in the country is the growing middle class. It is estimated that there will be a 150% increase in the number of middle class people. Due to rapid economic growth, Consumer markets in emerging market economies like India are growing.

The country’s modern consumption level is set to increase by 200% within a time span of 5 years to US$ 1.5 trillion. India is all set to experience high growth in consumer expenditure due to tremendous potential and its huge population. Also, the macro trends for the sector look favorable due to the country’s large ‘young’ population and high domestic consumption. In today’s scenario products categories like jewelry, food, shoes etc are slowly becoming lifestyle products, due to the increasing purchasing power of Indian urban consumer.

 

This is the right time that Indian retailers should take advantage of, and should diversify and try new formats and should build strong and new brands. One can attain sustainable competitive advantage by translating core values combining products, image and reputation into a coherent retail brand strategy.

 

Organized retail penetration and key trends across categories

Retail category

Category share as a % of total market 2014-15

ORP (%)

Approx. gross Margin (%)

Key trends

Food & beverage

69-70

2-3

3-14

Large market and low ORP presents robust opportunities

Clothing and textile

11-13

17-20

35-50

High margins, increased preference for branded apparel

Consumer durables

4-5

15-20

10-20

Wide range of price points and good-after sales service are key differentiators

Home décor and furnishing

3

5-6

40-50

Housing boom and increasing aspiration levels are driving demand

Beuty, personal care

8-11

6-10

20-40

Growth driven by new product launches, consumers’ aspirations and expansion plans of organized players

Footwear

2

16-17

25-35

Lifestyle brands are increasing their product offerings and formats

Others

3-4

9-30

10-15

Pharmacy retail, stationery retailers, etc

Figure 1: Penetration of Organized Retail and Key Trends

Source: Ministry of statistics and program implementation, A report on “Retail reforms in India’ by PwC, TechSci Research

Note: ORP – Organized Retail penetration

 

 

 

1.1 NEED FOR THE STUDY:

Changing trends in retail industrialization, brand internationalization and consumption behaviors come along with the change in how people shop. One of the main changes is shift in consumers, expectations wherein they perceive  shopping experience by itself is a pleasant one instead of just a chore depending upon them being an utilitarian or hedonic shopper.Each retailer  has to develop his  own strategy based on his or her retail store format with regard to store atmospherics particularly resting areas in terms of creating differentiation within the format as compared to the competitors, as out of the conventional 4 Ps of marketing three Ps viz Product, Pricing and promotion can no more be the only source of competitive advantage.

 

2. LITERATURE REVIEW:

The driving force behind shopping is the answer to the question “why do people shop?” The answer for the question can be obtained by examining the consumer purchasing/shopping motives. Motivation refers to the drive, urge, wish, or desire that leads to a goal-oriented behavior (Patel and Sharma, 2009). In laymen’s language these are nothing but the reasons for an individual to leave home for shopping. There might be several drives for individuals to go for shopping. Consumers are not interested in the actual products or services that a store offers, they are interested only in the benefits that they gain out of it. Some get satisfied just in purchasing what they had planned for, these types of individuals are called as Utilitarian shoppers (Tauber, 1972). They pay less attention to the decorations or the extra add on facility which the store offers, these are considered to be irrelevant to their shopping objectives and motives (Fischer) whereas others, the non-utilitarian or the hedonic look for fun, entertainment and rest during shopping (Babin, Darden, and Griffin, 1994).

 

There are many type of retail formats, of which the largest in India are the Shopping Malls. According to Mohammed Ismail El-Adlys research there are three main factors which attributed to Shopping malls attractiveness. They are Comfort, Entertainment, Diversity and Mall Essence. The factor comfort is the most significant factor among all and has α value of 0.794. There are seven attributes under the comfort factor, which are the mall security, parking space, comfort, width, cleanness, and seating/resting space (El-Adly, 2007). Also, (Nicholls, Li, Kranendonk, and Roslow, 2002) found out that today’s mall shoppers are leisure in nature than that of the 90’s. They usually shop on weekends and on average spend about 2-3 hours in a store. In contrast to this, (Yavas, 2003) experiment/ research shows that both the considered shopper segments view Availability of Seats, rest areas in the mall as least important factor when it comes to choosing between two malls. “Impulse buying behavior is an enigma in the marketing world, for here is a behavior which the literature and consumers both state is normatively wrong, yet which accounts for a substantial volume of the goods sold every year across a broad range of product categories” (Hausman, 2000). The sales of a particular store would increase if there are more number of hedonic buyers who are more likely to engage in impulse buying. The research by (Smith, Sherman, and Mathur, 1997) confirms that not only the cognitive factors but also the in-store environment and the emotional state of consumers are responsible for store selection and their purchase behavior. So it is vitally important to acknowledge and provide sufficient aesthetics inside the store to satisfy the customers. The satisfied custome rs not only give repeat purchases but also ensures to do his bit of word of mouth propaganda which in turn brings new customers to the stores (Singh, Katiyar, and Verma, 2014).

 

 

According to (Applebaum, 1951) “To buy is to purchase. To shop is to visit business establishments for inspection or purchase of goods”.  And not always only the purchaser visits the store. Many a times there will be bundle carrier as well, like mom accompanying a kid in buying. Though the decision maker is the kid, the parent is the one who pays for it. So it essential to account the needs of the bundle carrier as well. (OXENFELDT, 1975)Says that, consumers tend to have both opinions and feelings towards each store, which would ultimately lead to a decision making. So it is vitally important to build a good store image in the minds of the consumers. In order to do that a holistic approach has to be adopted which takes care of the products variety, assortment and availability, competitive pricing and the store atmospherics.

 

(Store Atmospherics Provide Competitive Edge, 2005)suggests that there are three important parameters that decide the attractiveness of a retail store, in the eyes of a customer are: 1)the cleanliness associated with the store 2)passive atmospherics which includes the lighting, temperature, aisle width etc.3) the active atmospherics which includes the music and I store TV. The younger customers have an inclination towards the active atmosphere while the affluent mature customers are inclined towards the passive atmosphere of the retail stores. (Lunardo and Roux, 2014) Says consumers feel an overly arousing store environment is a deception to entice them to buy. With a change in the traditional landscape of retail store which is marked by the dwindling of the mom and pop store and the rise of organized retail store, establishing a store image has become ubiquitous for the owners. Store image is blend of tangible and intangible attributes (Color and décor of the interiors of the outlet, music played inside the outlet, crowding and lighting within the outlet, design, layout, signage, olfactory factor, and tactile factor.)

 

This article of (Sen and Srivastava, 2016) throws light on how cultural conditioning influences the consumption behavior of customers. Customers who were highly conditioned by culture preferred a utilitarian product over a hedonic one, while consumers who belonged to a region that was relatively less conditioned by culture, preferred hedonic over utilitarian products but did not perceive them as being different from utilitarian products in terms of brand personality. Preferences for utilitarian and hedonic products depend on decision targets. (Lim and Ang, 2008) Consumers deciding for others were more likely to choose hedonic over utilitarian options than were consumers deciding for them selves. (Lu, Liu, and Fang, 2016) casts a light on how both the utilitarian and hedonic aspects of a self-service experience influence a consumer’s future behavioral intentions with the technology. Three variables were found to influence a consumer’s utilitarian value: ease of use, perceived control, and functionality. Two variables were found to influence hedonic value judgments: need for human interaction and personal innovativeness in information technology. Retailers trying to implement self-service technology must not only be mindful of the benefits or utility of the technology, but also how the consumer perceives the process or enjoyment of using the technology.

 

2.1 RESEARCH GAP:

Prior research in the field of marketing has supported the relationship between various in-store attributes like color, music, lighting, crowd etc. However there are no studies pertaining to consumer buying traits and interrelations with resting area under different retail formats.

 

3. STATEMENT OF THE PROBLEM:

In today’s scenario one of the store managers’ KRA would be to ensure optimum sales through conversions of walk-ins. To do this it is crucial to create resting areas and atmospherics as a strategic differentiator by aligning it to different segment of consumers aligned to their traits.

 

3.1.1 OBJECTIVES:

To analyze the behavior of customers in different store formats and classify them into utilitarian and hedonic shoppers. To analyze the impact of resting areas on consumer’s store choice decision on different types of retail formats

 

3.1.2 HYPOTHESIS:

H0: There is no significant difference between an utilitarian and an hedonistic shopper.

H1: There is significant difference between an utilitarian and an hedonistic shopper.

H0: There is no significance difference in store choice decision due to the resting areas in different retail stores under FMCG, Sports, Apparel, Book, Jewelry.

H1: There is significance difference in store choice decision due to the resting areas in different retail stores under FMCG, Sports, Apparel, Book, Jewelry.

 

4. RESEARCH METHODOLOGY:

300 Retail shoppers above the age of 17 are the sample of the study drawn from different gender, marital status, income level, etc. A survey of 300 retail shoppers selected randomly as the sample size using convenience sampling was conducted and frequency analysis,  cluster analysis and one way Anova were used to identify consumer traits and impact of resting area store choice decision factors.

 

 

4.1 STATISTICAL TOOLS ADOPTED FOR THE STUDY:

4.1.1Frequency Analysis:

To understand relationship between demographics and traits.

 

4.1.2 Cluster Analysis:

To understand consumer traits and segment under utilitarian or Hedonistic traits.

 

4.1.3 One Way Anova:

To compare the effect/importance of resting areas under different retail formats.

 

4.1.4 Limitations of the study:

The sample population were primarily only from the Bangalore Location, so the results can be different when the samples are collected from different geographies.

 

5. DATA INTERPRETATION AND ANALYSIS:

5.1      Respondents profile:

5.1.1 Age:

Age of the respondents is one of the most important characteristics in understanding their views about the particular problems; by and large age indicates level of maturity of individuals in that sense age becomes more important to examine the response

 

 

Table-5.1.1 Age wise respondent profile

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Age

42

14.2

14.2

14.2

22 – 29

98

33.2

33.2

47.5

29 – 36

83

28.1

28.1

75.6

36 - 60

49

16.6

16.6

92.2

Above 60

23

7.8

7.8

100.0

Total

295

100.0

100.0

 

Source: Primary Data

 

 

It is quite clear that out of the total respondents investigated for this study, a majority (33.2 per cent) of them were in the age bracket of 22-29 years whereas about 28 per cent were found to fall in the age bracket of 29-36. Meager but valuable responses came from the above 60 years old respondents which constitutes a 7.8% of total respondents.

 

5.1.2 Gender:

Out of the overall responses, about 45 percent of them were males and 53.9 percent were females. And also there were a total of 2 responses in other category which contributes 0.7% of overall responses.

 

Table-5.1.2 Gender wise respondent profile

Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

134

45.4

45.4

45.4

Female

159

53.9

53.9

99.3

Others

2

.7

.7

100.0

Total

295

100.0

100.0

 

Source: Primary Data

 

5.1.3         Marital Status:

Table-5.1.3 marital status wise respondent profile

Marital Status

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Single

115

39.0

39.0

39.0

Married

180

61.0

61.0

100.0

Total

295

100.0

100.0

 

Source: Primary Data

 

The number of married responses was almost 1.5 times more than the number of single respondents. Since the category of stores selected attracts more married women, they eventually had a majority in the frequency analysis.

 

5.1.4         Income:

The majority of the respondents’ income seems to lie between 5-20. This tells us that, the respondents have a good buying power. Also 13.9% of them had a income less than 3LPA which also includes students who don’t earn at all.

 

Table-5.1.4 Income wise respondent profile

Income

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

< 3

41

13.9

13.9

13.9

3 – 5

45

15.3

15.3

29.2

5 – 10

103

34.9

34.9

64.1

10 – 20

98

33.2

33.2

97.3

> 20

8

2.7

2.7

100.0

Total

295

100.0

100.0

 

Source: Primary Data

 

5.2 Cluster Analysis:

The cluster membership table below shows the classification of the respondents into two.

 

 Table -5.2.1 Cluster Membership Table

Cluster Membership

Case

2Clusters

Case

2 Clusters

Case

2 Clusters

Case

2 Clusters

Case

2 Clusters

1

1

21

2

41

1

61

1

81

2

2

1

22

2

42

1

62

1

82

2

3

1

23

2

43

1

63

1

83

2

4

1

24

2

44

1

64

1

84

2

5

1

25

2

45

1

65

1

85

2

6

1

26

2

46

1

66

1

86

2

7

1

27

2

47

1

67

1

87

2

8

1

28

2

48

1

68

1

88

2

9

1

29

2

49

1

69

1

89

2

10

1

30

2

50

1

70

1

90

2

11

1

31

2

51

1

71

1

91

2

12

1

32

2

52

1

72

1

92

2

13

1

33

2

53

1

73

1

93

2

14

1

34

2

54

1

74

1

94

2

15

1

35

2

55

1

75

1

95

2

16

1

36

2

56

1

76

1

96

2

17

1

37

2

57

1

77

1

97

2

18

1

38

2

58

1

78

1

98

2

19

1

39

2

59

1

79

2

99

1

20

2

40

1

60

1

80

2

100

1

101

1

121

1

141

2

161

1

181

1

102

1

122

1

142

2

162

1

182

1

103

1

123

1

143

2

163

1

183

1

104

1

124

1

144

2

164

1

184

1

105

1

125

1

145

2

165

1

185

1

106

1

126

1

146

2

166

1

186

1

107

1

127

1

147

2

167

1

187

1

108

1

128

1

148

2

168

1

188

1

109

1

129

1

149

2

169

1

189

1

110

1

130

1

150

2

170

1

190

1

111

1

131

1

151

2

171

1

191

1

112

1

132

1

152

2

172

1

192

1

113

1

133

1

153

2

173

1

193

1

114

1

134

1

154

2

174

1

194

1

115

1

135

1

155

2

175

1

195

1

116

1

136

1

156

2

176

1

196

1

117

1

137

1

157

2

177

1

197

2

118

1

138

2

158

1

178

1

198

2

119

1

139

2

159

1

179

1

199

2

120

1

140

2

160

1

180

1

200

2

201

2

221

1

241

1

261

2

281

1

202

2

222

1

242

1

262

2

282

1

203

2

223

1

243

1

263

2

283

1

204

2

224

1

244

1

264

2

284

1

205

2

225

1

245

1

265

2

285

1

206

2

226

1

246

1

266

2

286

1

207

2

227

1

247

1

267

2

287

1

208

2

228

1

248

1

268

2

288

1

209

2

229

1

249

1

269

2

289

1

210

2

230

1

250

1

270

2

290

1

211

2

231

1

251

1

271

2

291

1

212

2

232

1

252

1

272

2

292

1

213

2

233

1

253

1

273

2

293

1

214

2

234

1

254

1

274

2

294

1

215

2

235

1

255

1

275

2

295

1

216

2

236

1

256

2

276

1

 

 

217

1

237

1

257

2

277

1

 

 

218

1

238

1

258

2

278

1

 

 

219

1

239

1

259

2

279

1

 

 

220

1

240

1

260

2

280

1

 

 

Profile of Cluster 1:

 

 

 

Table-5.2.2 Profile of Cluster 1

Trend setter

Educate oneself about new arrivals

Visit new otlets

Loner

Multiple choices

Feel better

Enjoy shopping

Time pass

Fun and entertainment

4

4

3

3

2

2

4

3

3

4

3

4

4

4

3

3

2

4

3

4

2

1

4

3

4

3

2

4

4

3

4

2

2

2

4

3

3

3

2

1

4

4

4

2

3

 

Table 5.2.2 Continued

Relaxation

Social experience

Friends and family shopping

Shopping assistance

Background music

Unplanned purchase

Problem solver

Trend setter

Loneliness

Cluster

4

2

1

1

2

2

3

2

2

1

3

2

2

3

4

3

4

3

2

1

2

4

1

5

4

2

3

4

4

1

2

3

4

4

2

2

3

3

4

1

2

4

5

1

4

3

2

2

4

1

Profile of Cluster 2:

 

Table-5.2.3 Profile of Cluster 2

Time Consuming Process

Time saving

Value for money

No time

Brand and Store specific

Less time consuming

Nearby Stores

Lower Price

Cluster

5

4

4

5

4

5

3

5

2

3

3

5

3

4

5

3

3

2

3

4

3

3

4

4

4

5

2

4

4

3

4

3

5

5

4

2

3

5

4

4

5

4

4

5

2

The above table defines the properties of clusters. Cluster 1 captures all the respondents with hedonic behavior whereas cluster 2 captures all the respondents with utilitarian behavior.

 

5.3 One Way ANOVA:

Table-5.3.1Aniova Table – One Way Anova

ANOVA

Store Choice Decision 

 

Sum of Squares

Df

Mean Square

F

Sig.

Between Groups

38.495

4

9.624

122.153

.000

Within Groups

22.847

290

.079

 

 

Total

61.342

294

 

 

 

Since the significance value is less than 0.05, we reject H0, that is

H0: There is no significant difference in store choice decision due to the resting areas in different retail stores. (FMCG, Sports, Apparel, Book, Jewelry)

 

Table-5.3.2 Multiple Comparisons Table – One Way Anova

Multiple Comparisons

Dependent Variable:   Resting Areas 

Tukey HSD 

(I) Type of Store

(J) Type of Store

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

Set A

Set B

-.4350*

.08927

.000

-.6801

-.1900

Set C

1.4294*

.08927

.000

1.1843

1.6744

Set D

-.4124*

.08927

.000

-.6575

-.1674

Set E

1.1695*

.08927

.000

.9244

1.4145

Set B

Set A

.4350*

.08927

.000

.1900

.6801

Set C

1.8644*

.08927

.000

1.6194

2.1095

Set D

.0226

.08927

.999

-.2225

.2676

Set E

1.6045*

.08927

.000

1.3595

1.8496

Set C

Set A

-1.4294*

.08927

.000

-1.6744

-1.1843

Set B

-1.8644*

.08927

.000

-2.1095

-1.6194

Set D

-1.8418*

.08927

.000

-2.0869

-1.5968

Set E

-.2599*

.08927

.031

-.5049

-.0148

Set D

Set A

.4124*

.08927

.000

.1674

.6575

Set B

-.0226

.08927

.999

-.2676

.2225

Set C

1.8418*

.08927

.000

1.5968

2.0869

Set E

1.5819*

.08927

.000

1.3369

1.8270

Set E

Set A

-1.1695*

.08927

.000

-1.4145

-.9244

Set B

-1.6045*

.08927

.000

-1.8496

-1.3595

Set C

.2599*

.08927

.031

.0148

.5049

Set D

-1.5819*

.08927

.000

-1.8270

-1.3369

Based on observed means.

The error term is Mean Square(Error) = .235.                                        * The mean difference is significant at the .05 level.

Multiple comparisons table shows that the significance value for the combination Set A –D is very high (0.99) and the combination Set C-E is also greater than 0.01.

 

5.4  Frequency analysis

Table-5.4.1 Comparison of Cluster Groups with Demographic Factors

 

Single Linkage

Age

Gender

Marital Status

Income

Credit Card Usage

Time Spent

Weekday Time Preference

Weekend time preference

Shopping Frequency

1

N  Valid

195

195

195

195

195

195

195

195

195

Missing

0

0

0

0

0

0

0

0

0

Meaning

2.687

1.579

1.595

2.918

1.626

3.179

2.108

2.056

3.113

Median

2.000

2.000

2.000

3.000

2.000

3.000

2.000

2.000

3.000

Std. Deviation

1.1121

.5153

.5515

1.1231

.4957

1.1593

1.3560

1.3667

.9457

Skewness

.440

-.095

.549

-.366

-.395

-.196

-.022

-.066

-.339

Std. Error Skewness

.174

.174

.174

.174

.174

.174

.174

.174

.174

2

N  Valid

100

100

100

100

100

100

100

100

100

Missing

0

0

0

0

0

0

0

0

0

Meaning

2.740

1.500

1.700

3.030

1.690

3.140

1.780

2.130

3.580

Median

3.000

1.500

2.000

3.000

2.000

3.000

2.000

2.000

4.000

Std. Deviation

1.1944

.5025

.4606

.9688

.4648

1.1549

1.4040

1.3000

.9554

Skewness

.157

.000

-.886

-.673

-.834

-.159

0156

-.134

-.056

Std. Error Skewness

.241

.241

.241

.241

.241

.241

.241

.241

.241

 

 

Table -5.4.2 Credit Card Usage

Credit Card Usage

Single Linkage

Frequency

Percent

Valid Percent

Cumulative Percent

1

Valid

Yes

74

37.9

37.9

37.9

No

121

62.1

62.1

100.0

Total

195

100.0

100.0

 

2

Valid

Yes

31

31.0

31.0

31.0

No

69

69.0

69.0

100.0

Total

100

100.0

100.0

 

 

There is slight difference in the preference of credit card usage between the hedonic and utilitarian shoppers. More number of Utilitarian shoppers seem to prefer not using a credit card, where as there is a increase of 6.5% in the Hedonic shoppers who prefer using a credit card.

 

6.    FINDINGS:

6.1.1 The hedonic customers possessed qualities of being a trend setter who would like to visit various new stores frequently in order to keep themselves updated to latest styles. Also these types of shoppers like to have multiple choices, (i.e.) in order to buy one item; they would prefer having more choices. These are the type of shoppers who enjoy shopping; they would love to have fun and entertainment while shopping. They consider shopping as a social experience. They never get tiered so easily and these types of shoppers engage in impulse buying more. In store atmospherics like music etc. impresses these kinds of shoppers. They tend to feel relaxed and feel good after their shopping.

 

 

6.1.2 The other type of shoppers under study – Utilitarian Shoppers does not seem to enjoy shopping; rather they consider shopping as a task. These kinds of shoppers prefer shopping at nearby outlets and at places where they find good value for money. Generally these kinds of people do not have time for their normal work, they are always busy. They consider shopping as a time consuming purpose and so the frequency of shopping is also very less. The in store atmospherics or any other form of attraction doesn’t seem to grab their attention; the only factor which attracts them is low price.

 

6.1.3 Also when comparing the importance of resting areas in store choice decision making, there were considerable amount of difference among various categories of stores.

 

6.1.4 Book Store and jewelry store shared same level of importance in resting areas when it comes to store choice decision.

 

6.1.5 Similarly, Grocery store and Sports stores shared same level of importance in resting areas when it comes to store choice decision.

 

6.1.6 It is also found that the utilitarian shoppers do not prefer using a credit card for their purchases/ shopping, whereas the other type of shoppers – hedonic shoppers are, in comparison to utilitarian shoppers, use credit cards more.

  

6.1.7 The majority of the respondents who possessed the hedonic behavior were primarily males in the age group of 25 to 32 who were in thier early adulthood stage of life. The average income of this group of respondents was between 5 to 10 lakhs with most of them having an access and use credit cards. When it comes to shopping behavior during weekdays and weekends, no big difference can be found among these two.

 

6.1.8 The majority of the respondents who possessed the utilitarian behavior were also primarily males in the age group of 25 to 32. The difference comes here in the preference of shopping time when compared with the hedonic shoppers. Unlike them, the utilitarian shoppers preferred to shop during weekends. And these set of people are averse of using a credit card.

 

6.1.9 Seating availability is considered highly important in the Apparel, Books and Jewelry store is very essential.

 

6.1.10 Kids Play area is considered highly important in Book and Jewelry store.

 

6.1.11 Except for Sports store in all other categories of stores Wash rooms are considered to be highly important.

 

7.    RECOMMENDATIONS:

7.1.1 If the store is operating in Apparel/ Books and Jewelry, then certain amount of the floor space must be allocated for seating (chairs). Though this space doesn’t contribute directly to any sort of returns, it ensures delivering good shopping experience for the customers this making the store a preferred choice in the minds of the customers.

 

7.1.2 Managers must take into consideration that the presence of kids play area in a Jewelry/ Book store will let the actual customers shop more peacefully and thus make happy and informed choices. Play Area reduces the tension created by the kids of the customers thus letting them to shop peacefully.

 

7.1.3Washrooms are a must in all types of stores. Managers must ensure there are proper washrooms provided based on the number of customer walk-ins.

 

7.1.4If the store has products which attracts hedonic shoppers, managers must ensure that there are good product choices. Also as these shoppers go shopping all throughout the week without any time restriction, the products availability must be ensured all though out the week. And electronic payment systems must be made available as these are the group of people who use their credit cards extensively.

 

7.1.5 If the store has products which attract utilitarian shoppers, managers must ensure that there are adequate billing counters and there are no queues at the billing counters. Also, product stocking must be high during the weekends as this kind of shoppers’ turnout in large number during weekends. These kinds of stores must have adequate change (money) to ensure fast billing/ checkout process.

 

8.    CONTRIBUTION TO THE BODY OF KNOWLEDGE:

The primary aim of this study is to segment the consumers on the basis of utilitarian and hedonistic traits and garner insights into their perceptions about resting areas So far many studies have focused on other elements of store atmospherics affecting the store choice decision whereas this study has contributed to the understanding the retail industry’s type of customer, and the various factors which affect the customers store choice decision. It provides an in-depth analysis of the characteristics of Utilitarian and Hedonic Shoppers and underlines the importance of resting areas across multiple categories of retail stores. Further more it provides a useful basis to compare the importance of resting areas in 5 different categories of retail stores.

 

9.   CONCLUSION:

Objective was to identify traits that were responsible for the customer store choice decision particularly with respect to resting areas. Further with the help of frequency, cluster analysis the impact of the traits, demography on store choice decision was determined which will assist to strategize better and use resting areas as differentiator to compete aligned to specific retail format.

 

10. REFERENCES:

1.         Patel, V., and Sharma, M. (2009). Consumers’ Motivations to Shop in Shopping Malls: a Study of Indian Shoppers. (S. Samu, R. Vaidyanathan, and D. Chakravarti, Eds.) Association for Consumer Research, 8, 285-290. Retrieved from http://www.acrwebsite.org/volumes/14915/volumes/ap08/AP-08

2.         Applebaum, W. (1951). Studying Customer Behavior in Retail Stores. Journal of Marketing, 16(2), 172-178.

3.         Babin, B. J., Darden, W. R., and Griffin, M. (1994). Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value. Journal of Consumer Research, 20, 644-656.

4.         Bellizzi, J. A., Crowley, A. E., and Hasty, R. W. (1983). The effects of color in store design. Journal of Retailing.

5.         Chen, H.-S., and Hsieh, T. (2011, October 14). The effect of atmosphere on customer perceptions and customer behavior responses in chain store supermarkets. African Journal of Business Management, 5, 10054-10066.

6.         Collier, J. E. (2016). Examining customers’ intentions to use self-service technology through utilitarian and hedonic value judgments.

7.         El-Adly, M. (2007). Shopping malls attractiveness: a segmentation approach. International Journal of Retail and Distribution Management, 35, 936-950. doi:10.1108/09590550710828245

8.         Gopal, V., and Gopal, V. (2010). Impact of In-store Music on Shopper Behavior. Journal of Business and Retail Management Research, 5(1).

9.         Hausman, A. (2000). A multi-method investigation of consumer motivations in impulse buying behavior. The Journal of Consumer Marketing, 403-419.

10.       Hui, M. K., and Bateson, J. E. (1991). Perceived Control and the Effects of Crowding and Consumer Choice on the Service Experience. Journal of Consumer Research, 174.

11.       Hul, M. K., Dube, L., and Jean-Charles, C. (1997). The impact of music on consumers' reactions to waiting for services. Journal of Retailing, 87-104.

12.       Lim, E., and Ang, S. (2008, March). Hedonic vs. utilitarian consumption: A cross-cultural perspective based on cultural conditioning. Journal of Business Research, 61(3), 225.

13.       Lu, J., Liu, Z., and Fang, Z. (2016, July). Hedonic products for you, utilitarian products for me. Judgment and Decision Making,, 11(4), 332-341.

14.       Lunardo, R., and Roux, D. (2014). In-store arousal and consumers’ inferences of manipulative intent in the store environment. European Journal of Marketing, 49(5), 646-667.

15.       Nicholls, J., Li, F., Kranendonk, C. J., and Roslow, S. (2002). The seven year itch? Mall shoppers across time. Journal of Consumer Marketing, 19(2), 149-165. doi:http://dx.doi.org/10.1108/07363760210420568

16.       Olăhuţ, M. R., EL-Murad, J., and Plăiaş, I. (2012). Store atmosphere: Conceptual Issues and It’s Impact on Shopping Behavior. Marketing – from information to decision.

17.       Olsen, S. O., and Skallerud, K. (2011). Retail attributes’ differential effects on utilitarian versus hedonic shopping value. Journal of Consumer Marketing, 532-539. doi:10.1108/07363761111181527

18.       Oxenfeldt, A. R. (1975). Developing a favorable price-quality image. Journal of Retailing,

19.       Pandey, J., and Darla, A. (2012, April). A study on the influence of store level services on store. International journal of management research, 2(4).

20.       Retail Industry in India. (2016, December). Retrieved from IBEF: http://www.ibef.org/industry/retail-india.aspx

21.       Sen, A., and Srivastava, A. K. (2016, September). Students' Purchase Intention for Apparels An Empirical Study on Atmospherics of Selected Organized Retail Outlet of Bilaspur City. SUMEDHA Journal of Management, 5(3).

22.       Sharples, S. (1987). Lighting Up Time: Illumination in the Retail Environment. Retail and Distribution Management, 43.

23.       Singh, P., Katiyar, N., and Verma, G. (2014). Retail Shoppability: The Impact Of Store Atmospherics and Store Layout On Consumer Buying Patterns. International Journal Of Scientific And Technology Research, 3(8).

24.       Smith, R. B., Sherman, E., and Mathur, A. (1997). Store Environment and Consumer Purchase Behavior: Mediating Role of Consumer Emotions. Wiley Periodicals Inc., pp. 361-378.

25.       Smith, W. (1989). Trends in Retail Lighting: An Intelligent Design Approach. International Journal of Retail and Distribution Management, 30.

26.       (2005). Store Atmospherics Provide Competitive Edge. Chain Store Age.

27.       Tauber, E. (1972). Why Do People Shop? Journal of Marketing, 36, 46-49.

28.       Vida, I. (2008). The Impact Of Atmospherics On Consumer Behaviour: The Case Of The Music. Economic and Business Review for Central and South - Eastern Europe, 10(1), 21-35.

29.       Yalch, R., and Spangenberg, E. (1990). Effects Of Store Music On Shopping Behavior. The Journal of Services Marketing, 31.

30.       Yavas, U. (2003). A Multi-Attribute Approach to Understand Shopper Segments. International Journal of Retail and Distribution Management, 541-548.

 

 

Received on 29.10.2017                Modified on 02.11.2017

Accepted on 19.12.2017           ©A&V Publications All right reserved

Asian Journal of Management. 2018; 9(1):507-515.

DOI: 10.5958/2321-5763.2018.00079.3