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LAMPIRAN

Hubungan Faktor..., Bayu Singgih Kristian, FB UMN, 2014

Lampiran 1

SPBU Self Service Pertamina Dapat Respon Negatif

Selasa, 01 Januari 2013 15:48 wib | Fakhri Rezy – Okezone Ilustrasi. (Foto:

Okezone)JAKARTA –

PT Pertamina (Persero)

melakukan terobosan dengan

menerapkan stasiun pengisian

bahan bakar umum (SPBU)

tanpa petugas alias self

services. Sayangnya respon

masyarakat terhadap SPBU

ini tidak sepadan.

Pihak SPBU Pertamina Self Service mengatakan, masih banyak respon masyarakat yang menanggapi negatif,

lantaran awam akan keberadaan fasilitas tersebut. Terdapat beberapa keluhan dari masyarakat pengguna SPBU

tersebut.

"Ada yang bilang pelayanannya kurang bagus lah, terus masih pada awam," kata Pengawas SPBU Pertamina Self

Service 34-11405, Deden S kepada Okezone di Jalan Palmerah Utara Raya No56, Jakarta, Selasa (1/1/2013).

Oleh karena itu, perlu personel tambahan untuk melakukan sosialisasi di masyarakat. Deden mengatakan, ke

depan akan menambah personel untuk pengajaran dan sosialisasi agar minimal masyarakat sekitar mengerti.

Menurutnya, Pertamina akan tetap menerapkan SPBU self service walaupun mendapat komentar-komentar

miring dari masyarakat. "Ada juga yang komentar, sudah bayar tapi enggak dilayani," kata dia.


Lampiran 2

Di SPBU Ini Anda Bisa Isi Bensin Sendiri Rista Rama Dhany - detikfinance

Jumat, 15/11/2013 11:25 WIB

Jakarta -SPBU milik PT Pertamina (Persero)

atau Corporate Owned Corporate Operated

(COCO) Jalan Kuningan, Jakarta mulai

menerapkan layanan pengisian Bahan Bakar

Minyak (BBM) secara swalayan atau self

service. Sehingga pemilik kendaraan bisa

mengisi bensin sendiri ke kendaraanya setelah

membayar ke petugas.

“Sekarang di sini bisa isi bensin sendiri, jadi konsumen tinggal bayar di kasir, lalu mendapatkan

struk dan tinggal angkat nozel-nya masukkan ke tangki kendaraan," kata Ardi salah satu petugas

SPBU COCO Kuningan kepada detikFinance, Jumat (15/11/2013).

Ardi mengatakan konsep self service memang baru diterapkan sejak awal November 2013

khususnya di SPBU Kuningan. Beberapa SPBU Pertamina lainnya juga telah melakukan uji coba

sejak tahun lalu. "Ini baru diterapkan mulai 1 November lalu, namanya sistem self service," kata

Ardi.

Sistem self service di SPBU Kuningan, hanya berlaku untuk pengisian BBM untuk sepeda motor

saja, untuk mobil dan kendaraan lainnya belum diterapkan. Alasannya karena sistemnya masih

baru, juga sambil menunggu para pengendara sepeda motor lebih terbiasa agar lancar.

"Sistem ini membuat antrean kendaraan yang mengisi bensin di SPBU jauh lebih sedikit, karena

dengan pelanggan mengisi sendiri jauh lebih cepat," katanya.

Ardi mengakui awalnya penerapan sistem self service banyak masyarakat yang bingung, bahkan

tidak jarang tetap memilih dilayani sendiri oleh petugas SPBU seperti pengisian BBM pada

umumnya. "Ya karena banyak yang bingung, takut kalau salah-salah nozelnya mengeluarkan

bensin terus, jadi awalnya ya banyak yang nggak mau," ungkapnya. Ardi menambahkan namun

dengan penjelasan petugas SPBU bahwa sistem self service ini lebih praktis dan lebih cepat,

banyak konsumen yang sudah mulai terbiasa.

"Jadi pada saat pelanggan ngantre panjang kami kasih tahu kalau dengan sistem self service ini

jauh lebih cepat dan antreannya sedikit, makanya banyak yang coba, kalau ada yang bingung ada

petugas kami yang mengawasi dan siap membantu," katanya.

Penerapan sistem ini membuat banyak nozel SPBU yang berfungsi sehingga antrean kendaraan

lebih sedikit. "Biasanya di bagian sepeda motor hanya 2-4 petugas SPBU yang melayani pengisian

BBM, tapi dengan sistem self service ini semua nozel SPBU berfungsi semua, jadi seperti ada 8-

10 nozel SPBU yang siap mengisi BBM kendaraan konsumen," ucapnya.


http://finance.detik.com/read/2012/08/06/204952/1984681/1034/ini-dia-lokasi-lokasi-spbu-swalayan-pertamina

Lampiran 3

Kuesioner Pengaruh Demografis

dan Karakteristik Konsumen

terhadap penggunaan Teknologi

Retail Self Service Pertamina Program Studi Manajemen – Fakultas Ekonomi

Universitas Multimedia Nusantara

Jln. Boulevard Gading Serpong

Tangerang – Banten

www.umn.ac.id

Yth,Responden,

Saya mahasiswa semester akhir prodi Manajemen UMN yang sedang menyusun skripsi mengenai

“Pengaruh Faktor demographic dan perilaku konsumen terhadap Penggunaan Retail Self Service”.

Diharapkan penelitian ini dijawab sesuai dengan realita atau dalam keadaan sejujurnya, dikarenakan

tidak ada jawaban benar atau salah dalam pengumpulan data ini. Seluruh data yang terkumpul dalam

kuesioner ini adalah untuk keperluan akademis dan akan dijaga kerahasiaannya dengan tidak

dipublikasikan. Atas partisipasi responden, saya mengucapkan terima kasih.

Tertanda,

Bayu Singgih Kristian

10130110015

1. Jenis kelamin : Pria Wanita

2. Umur : 17-27 tahun 38-47 tahun 56 ke atas

28-37 tahun 48-55 tahun

3. Pendidikan SMP SMA Pasca Sarjana (S2/S3)

Terakhir :

a

s

s

d

g

g


http://www.google.com/url?q=http%3A%2F%2Fwww.umn.ac.id&sa=D&sntz=1&usg=AFQjCNFZxmm3lc67W1MXBo89Jd5m3aKcwg

Diploma Sarjana ( S1)

4. Pekerjaan : Pelajar / Mahasiswa PNS Lainnya : …………

Swasta Wirausaha

5. Pendapatan tiap: 200,000-1.000.000 5.000.000-15.000.000

bulan

1.000.000- 5.000.000 15.000.000 ke atas

6. Apakah anda pernah melakukan pengisian di SPBU Pertamina dengan sistem Isi Sendiri (SST)

tersebut?

Pernah Belum Pernah

Untuk pernyataan-pernyataan berikut ini, Bapak/Ibu/Saudara/Saudari dipersilahkan untuk memberikan

jawaban dengan mengisi tanda centang (√) pada kolom jawaban yang sudah tersedia dengan pilihan

sebagai berikut :

1. Sangat Tidak Setuju (STS) 4. Setuju (S)

2. Tidak Setuju (TS) 5. Sangat Setuju (SS)

3. Netral (N)

A. Dimensi Kecemasan Teknologi

No Pernyataan Pilihan Jawaban

STS TS N S SS

1 Saya menghindari teknologi SST Pertamina karena hal tersebut tidak

familiar untuk saya

2 Saya kesulitan untuk memahami hal-hal yang berbau teknologi

3 Saya yakin dengan kemampuan saya untuk mengerti fungsi dari suatu

teknologi

4 Saya cukup percaya diri untuk belajar meningkatkan kemampuan saya

mengenai suatu teknologi baru

5 Ketika saya diberi kesempatan untuk menggunakan teknologi, saya takut

jika saya dapat merusak teknologi tersebut.

6 Berbagai Istilah dalam suatu teknologi terdengar seperti suatu hal

membingungkan bagi saya

7 Saya ragu-ragu untuk menggunakan teknologi karena takut membuat

kesalahan yang tidak dapat saya tangani

8 Saya dapat menggunakan teknologi-teknologi penting yang mutakhir

9 Saya merasa khawatir untuk menggunakan teknologi

D


B. Dimensi Kebutuhan Interaksi


STS TS N S SS

1 Saya suka berinteraksi dengan orang yang menberikan pelayanan kepada

konsumen

2 Saya cukup terganggu ketika harus menggunakan mesin saat saya

seharusnya dapat berinteraksi dengan penyedia jasa layanan tersebut

3 Perhatian secara personal dari karyawan penyedia layanan tidak terlalu

penting untuk saya

4 Kontak secara langsung dengan penyedia jasa membuat saya lebih

menikmati proses penyaluran jasa tersebut

C. Dimensi Teknologi Inovasi


STS TS N S SS

1 Saya akan membeli/menggunakan suatu barang dengan teknologi yang

tinggi sebelum orang lain mengetahui keberadaan barang tersebut

2 Akan sangat membanggakan ketika menjadi orang pertama yang

memiliki suatu teknologi baru

3 Saya mendapat dorongan dari dalam diri saya, setiap ada teknologi baru

yang muncul untuk dapat memilikinya

4 Menjadi yang pertama untuk membeli suatu alat teknologi baru adalah

hal yang penting untuk saya

5 Saya ingin memiliki sendiri produk teknologi yang paling terbaru

D. Dimensi Intention


STS TS N S SS

1 Saya berniat untuk menggunakan teknologi Self Service Pertamina dalam

6 bulan ke depan

2 Dalam 6 bulan ke depan saya akan berniat untuk lebih sering

menggunakan teknologi Self Service yang disediakan Pertamina

3 Saya menghindari menggunakan SPBU Pertamina yang memiliki

teknologi Self Service dalam 6 bulan ke depan


Lampiran 4

Construct Items

Technology anxiety TA01 I have avoided technology because it is unfamiliar to me

TA02 I have difficulty understanding most technological matters

TA03 I am sure of my ability to interpret technological output (r)

TA04 I am confident I can learn technology-related skills (r)

TA05 When given the opportunity to use technology, I fear I might damage it in

some way

TA06 Technological terminology sounds like confusing jargon to me

TA07 I hesitate to use technology for fear of making mistakes I cannot correct

TA08 I am able to keep up with important technological advances (r)

TA09 I feel apprehensive about using technology

Need for interaction NI01 I like interacting with the person who provides the service

NI02 It bothers me to use a machine when I could talk with a person instead

NI03 Personal attention by the service employee is not very important to me

NI04 Human contact in providing services makes the process enjoyable for me

Technological

Innovativeness

TI01 I get a kick out of buying new high tech items before most other people kno

w they exist

TI02 It is cool to be the first to own new high tech products

TI03 I get a thrill out of being the first to purchase a high technology item

TI04 Being the first to buy new technological devices is very important to me

TI05 I want to own the newest technological products

Intention K_BI01 I intend to use the self-checkout in the next 6 months

K_BI02 In the next 6 months I intend to use the self-checkout frequently


Lampiran 6

Screenshoot Kuesioner Google Docs


The influence of consumer traitsand demographics on intention

to use retail self-servicecheckouts

Hyun-Joo LeeOklahoma State University, Tulsa, Oklahoma, USA

Hyeon Jeong ChoUniversity of North Carolina, Greensboro, North Carolina, USA

Wenwen XuOklahoma State University, Tulsa, Oklahoma, USA, and

Ann FairhurstUniversity of Tennessee, Knoxville, Tennessee, USA

Abstract

Purpose – The purpose of this paper is to explore the relationships among demographic factors(gender, age, education, and income), consumer traits (technology anxiety, need for interaction, andtechnology innovativeness), and intention to use retail self-checkouts.

Design/methodology/approach – A total of 285 usable responses are obtained through a web-basedsurvey after excluding non-qualified respondents. Structural equation modeling is developed and tested.

Findings – The results of this paper demonstrate that demographic factors only indirectly influenceintention to use retail self-checkouts through consumer traits and thus the authors conclude thatindividual differences in the use of retail self-checkouts can be attributed to consumer traits which aredetermined by some of the demographic factors.

Research limitations/implications – Demographic factors and consumer traits are only includedas determinants of intention to use retail self-checkouts. Therefore, future research could attempt todraw a comprehensive picture of retail self-checkouts by incorporating other relevant factors.

Originality/value – By classifying individual difference traits into demographic factors andconsumer traits, this paper provides more detailed explanations of the relationships amongdemographic factors, consumer traits, and intention to use retail self-checkouts.

Keywords Consumer behaviour, Demographics, Personality, Self-service

Paper type Research paper

IntroductionIn response to rapid development of technology, retailers increasingly considerinnovative and interactive technological interfaces such as self-service technologies(SSTs) in the service delivery. The SST implies that people themselves perform tasksusing technologies without direct personal assistance in the consumption context(Meuter et al., 2000). Among various types of SST, retail self-checkouts have grown at afast pace over the past five years (Holman and Buzek, 2007). Retail self-checkouts arecomputerized systems that allow shoppers to scan, bag, and pay for items either bythemselves or with minimal assistance from a cashier at retail stores (Alpert, 2008).

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0263-4503.htm

MIP28,1

46

Marketing Intelligence & PlanningVol. 28 No. 1, 2010pp. 46-58q Emerald Group Publishing Limited0263-4503DOI 10.1108/02634501011014606


Food Marketing Institute indicates that almost 56 percent of grocery retailers installedself-checkouts in 2005, increasing from 38 percent in 2004. In 2006, more than $137billion was spent at self-service checkouts, up 24 percent over the prior year (Porjes,2008). Moreover, self-checkout’s growth has now moved to other retail formats. Forexample, do-it-yourself stores, such as Home Depot, have had self-checkouts since 2002(Morphy, 2002). In the IDC research in 2003, 44 percent of the respondents across fivecountries (i.e. USA, UK, Germany, Italy, and Australia) report that they prefershopping at retail stores that offer self-service checkout options (NCR, 2003).

Retail self-checkouts bring considerable benefits to consumers as well as to retailers.For retailers, the potential operational cost reduction can be the primary motive behindthe increasing installation of self-checkouts (Bitner et al., 2002). Among consumers,speed is reported as the main reason for choosing self-checkouts over personalassistance in the retail environment (Alpert, 2008). Given that consumers today arehighly sensitive to the speed of service delivery (Bateson, 1985), self-checkouts seem tosatisfy those consumers better when there is a long line at cashier lanes. Also,consumers who do not want to interact with cashiers often use self-checkouts. Inaddition, providing more choices of payment, greater privacy and control, and moreconvenience are the main reasons consumers use self-checkouts (Alpert, 2008).

Although the introduction of self-checkouts opens up benefits for consumers andretailers alike, some consumers respond with resistance to adopt retail self-checkouts.Since consumers, in the SST environments, should become an active player in servicedelivery (Anitsal and Schumann, 2007), the adoption of retail self-checkouts depends asa great deal on individual difference traits as on self-checkout design features (e.g. howeasy it is to use) (Harrison and Rainer, 1992). To understand consumers’ adoption ofSST, therefore, several empirical studies have investigated what types of individualtraits are related to the adoption of SST (Curran and Meuter, 2005; Weijters et al., 2007).

Individual difference traits have been classified into demographic/socioeconomicfactors and consumer personality traits (Schaninger and Sciglimpaglia, 1981).Demographic/socioeconomic factors have long been used to profile consumer groupsbecause firms can present more precise adjustment of service and marketing relatedwith specific target-market segments. For example, given that early adopters of newtechnology products are generally young and male consumers (Lu et al., 2003),marketers can portray a situation where young people or males actively use newtechnology products in advertisements. In addition to demographic factors, consumerpersonality traits notably influence the adoption of SST (Dabholkar, 1996; Meuter et al.,2005). Previous studies have examined a variety of consumer traits, such as technologyanxiety, self-efficacy, novelty seeking, and need for interaction, as the antecedents ofconsumer adoption of SST (Dabholkar and Bagozzi, 2002; Elliott and Hall, 2005;Meuter et al., 2005). Understanding how individual differences in consumercharacteristics influence the adoption of retail self-checkouts may help retailersdetermine whether to install retail self-checkouts, to which type of consumer is prone touse such options, and how to appeal to different consumer groups.

Conceptual framework and research hypothesesDemographics have been the subject of numerous studies as predictors of adoptionbehavior (Im et al., 2003; Meuter et al., 2005). However, in spite of this attention, theireffects on technology adoption are found to be less influential or often conflicting.

Consumertraits and

demographics

47


The significant effect of age is found with respect to the adoption of SST (Dean, 2008)whereas its effect is not significant in other studies (Weijters et al., 2007). On the otherhand, consumer traits have provided a more useful explanation than demographic orpsychographic factors in understanding why consumers use SST (Dabholkar andBagozzi, 2002). Based on this argument, we propose that demographic factors andconsumer traits interact with each other and determine consumers’ intention to useretail self-checkouts. Although demographic effects are known to be weak, weincorporate a number of demographic factors because of their extensive presence inadoption literature. In addition, demographic factors are easy to measure and readilyavailable, which facilitates the implementation of marketing strategies to targetconsumer groups (Weijters et al., 2007).

A comprehensive framework linking individual difference traits to technologyadoption has been lacking, particularly for SST. Thus, this paper is intended as aninvestigation of how individual differences in consumer characteristics affect intention touse retail self-checkouts. Furthermore, by decomposing individual difference traits intodemographic factors and consumer traits, we attempt to explore whether demographicfactors directly influence intention to use retail self-checkouts or indirectly influenceintention to use retail self-checkouts through consumer traits. As shown in Figure 1, weinvestigate the three links between demographic factors (i.e. gender, age, education, andincome), consumer traits, and intention to use retail self-checkouts. Three consumer traits(i.e. technology anxiety, need for interaction, and technology innovativeness) are includedin the present investigation because of their existence in recent technologyproducts/services research. Technology anxiety is defined as a fear and apprehensionabout using all forms of technology (Meuter et al., 2003). Need for interaction is the extentto which consumers importantly perceive human interaction in service delivery(Dabholkar, 1996). Technology innovativeness refers to consumers’ motivation of beingthe first to adopt new technology-based goods and services (Bruner and Kumar, 2007).

Effects of demographic factors on consumer traitsGender. Gender differences have been consistently noted in technology adoption.Women show a higher level of computer phobia and anxiety and have less favorableattitudes toward technology than men (Todman, 2000). Women also reveal greatdiscomfort with SST and seem to lack both control over technology and confidence inusing SST (Elliott and Hall, 2005). Thus:

H1a. Technology anxiety is greater for women than for men.

Figure 1.Conceptual framework

Demographic factors Consumer traits

• Gender• Age• Education• Income

• Technology anxiety• Need for interaction• Technology innovativeness

H1 – H4

H5 H6Intention touse

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Bales (1970) suggests two different interaction styles: active task behavior (e.g. givingopinions, giving information) and positive social behavior (e.g. agreement, actingfriendly). Between the two interaction styles, women engage more in positive socialactivities than men (Wood and Karten, 1986). Women’s high need for social interactionhas been observed in various situations. Women send more interactive messageswithin a formal online learning environment and are more interested in all forms ofassistance by salespersons when shopping in a conventional store (Burke, 2002). Basedon the findings, need for interaction may more strongly relate to women than men:

H1b. Need for interaction is greater for women than for men.

Given that men tend to be an online shoppers, men are more likely to be innovative inthe domain of technology than women because online shoppers more frequently useATM cards, cellular phones, and television shopping (Pastore, 1999). In Elliott andHall’s (2005) study, men exhibit a greater level of technological innovativeness andhave more desire to use SSTs than women. Thus, we hypothesize the following:

H1c. Technology innovativeness is greater for men than for women.

Age. Older people tend to perceive a reduction in their own cognitive capabilities in theprocess of learning and have lower perceptions of self-efficacy with regard to cognitivefunctioning (Hertzog and Hultsch, 2000). As a result, many older people believe thatthey are “too old” to learn how to use technologies (e.g. computer). Consistently, it isfound that age has the most significant and negative influence on technology anxietyamong various demographics (Simon and Usunier, 2007). Thus:

H2a. As age increases, technology anxiety increases.

Since the elderly are especially prone to feel loneliness and depression, they tend toseek social stimulation in retail stores by interacting with store employees (Kang andRidgway, 1996). Therefore, older people who tend to feel lonely are likely to have anegative attitude toward depersonalized retailing service (Forman and Sriram, 1991).Older consumers report that they miss human interaction when making self-servicetransactions (Dean, 2008). Accordingly:

H2b. As age increases, need for interaction increases.

Previous studies provide the evidence that highly innovative people tend to be youngin age (Im et al., 2003). That is, younger people are relatively early adopters of newideas, service, and products. Im et al. (2003) find that younger consumers own moreelectronic products that were considered as new and innovative products at the time ofthe study. Therefore, we hypothesize that younger people are likely to have greatertechnology innovativeness compared to older people. Thus, we expect the following:

H2c. As age increases, technology innovativeness decreases.

Education. Weijters et al. (2007) suggest that highly educated people are likely to beexposed to SST (e.g. employee-benefits intranet system and web-based customersupport site) not only at their workplaces but also in their day-to-day activities. Thus,they tend to gain more experience of using such new technology. On the other hand,results from Porter and Donthu (2006) show that insufficient knowledge is one of themain reasons why less-educated people choose not to use technology (e.g. internet)

Consumertraits and

demographics

49


because it makes them to feel anxious. Given that technology anxiety decreases as theuse of SST increases, we assume that highly educated people who seem to have moreexperience with technology are likely to have lower technology anxiety:

H3a. As education level increases, technology anxiety decreases.

Consumers who are trying to be early adopters of new technology can be characterizedby educational attainment because people’s way of gathering and processing is highlydependent upon education level (Im et al., 2003). According to Weijters et al. (2007),highly educated people tend to rely on more information before making a decisionwhereas less-educated people draw on fewer information cues. Therefore, we assumethat compared to less-educated people, highly educated people are easier to understandhow technology is processed and how it can be accessed, which in turn help them adoptnew technology. Thus, we hypothesize the following:

H3b. As educational attainment increases, technology innovativeness increases.

Income. Porter and Donthu’s (2006) study shows that using the internet lookscostly to people with a low income, because they have to purchase an internet accessdevice and pay ongoing access fees. On the other hand, people with a high income havethe ability to own technology products (e.g. personal computer and iPod), which makethem to have more usage experience with technology products. Since people on a lowincome may have limited usage experience with technology, it is likely that they havemore concerns about how to use technology and thus create an anxiety-provokingsituation with perceived difficulty. Therefore, we expect the following:

H4a. As income level increases, technology anxiety decreases.

Previous studies show that innovators tend to earn a high income and people with ahigh income are more likely to own new technology products (Im et al., 2003). InManning et al. (1995) study, innovators are defined as people who have an inherentdesire to seek novelty and creativity. Thus, affluent people who have more ability andmotivation to adopt new technology products seem to have more chances to be earlyadopters of new technology products:

H4b. As income level increases, technology innovativeness increases.

Effects of demographic factors on intention to use retail self-checkoutsPrevious studies suggest that adoption of technology-based products or services isrelated to consumers’ demographics. There is general consensus that consumers whotry to use new products or technologies tend to be younger, men, better educated, andhave a higher level of income (Im et al., 2003; Meuter et al., 2005). With regard to SST,age seems to be the strongest factor that affects usage behavior of SST. Youngerconsumers are more likely to use various SST (e.g. self-service checkout, internetbanking and ATM) than older consumers (Dean, 2008; Simon and Usunier, 2007).Effects of gender, income, and education are less definitive. Nilsson (2007) reportsgender differences in usage behavior of SST among Estonians; men tend to be internetbanking users, have a longer history of internet banking usage, and use it more often.However, in Sweden, there is no gender difference in internet banking usage. Incomeand education are significant factors in predicting customer usage of SST among

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Estonian consumers while the effects do not hold for Swedish consumers. In this study,we posit that:

H5. Demographic factors including: (a) gender, (b) age, (c) education, and (d)income are significantly related to intention to use retail self-checkouts.

Effects of consumer traits on intention to use retail self-checkoutsMeuter et al. (2003) find that technology anxiety is more influential in predictingadoption of a wide range of SST than demographic factors. It is also demonstrated thatconsumers who are less-technologically anxious are more likely to use SST (Oyedeleand Simpson, 2007). Thus, in line with this result, we suggest the following hypothesis:

H6a. Technology anxiety has a negative effect on intention to use retail self-checkouts.

Personal contact is important to consumers with a high need for interaction. Given thatusing SST minimizes interpersonal interactions, SST may not be regarded as anappealing option for those consumers. In this regard, the need for interaction is foundto negatively influence the use of SST (Dabholkar, 1996; Meuter et al., 2005). In thisstudy, we suggest that consumers with a high need for interaction look forward tointeracting with a store employee and they thus avoid using SST:

H6b. Need for interaction has a negative effect on intention to use retail self-checkouts.

Technology innovativeness is innovativeness specific to technology-based products orservices. Technology innovativeness has been identified as a significant predictor ofadoption of new technology-based products. It has also been determined that increasesin technology innovativeness result in increases in ownership of high-tech products(Hirunyawipada and Paswan, 2006). Based on this:

H6c. Technology innovativeness has a positive effect on intention to use retailself-checkouts.

MethodologySampling procedureData were obtained through a web-based survey from a consumer panel, which isrecruited and maintained by a market research firm specializing in consumer surveysover the internet. E-mail invitations were sent to members and a total of 437 membersaccessed the link for the survey. However, 152 of them were not qualified because theyhad not used a self-checkout at a retail store in the past six months, yielding 285 usableresponses. The web-based sample was deemed appropriate for this study for thefollowing reasons. First, use of a nationwide sample prevents the sample from beingcomposed of subjects from the same region and thus avoids any biases such asdemographic bias and regional availability of certain self-checkout systems (Meuteret al., 2003). Second, this study required that the sample have had prior usageexperience of self-checkouts. Given that the web-based sample is likely to be familiarwith technology-driven services (e.g. internet and SST), participants tend to haveadequate experience or exposure to self-checkouts, which makes it possible to includemore participants who meet the sample frame of this study. Analysis of demographicinformation revealed that respondents’ age ranged from 19 to 75 years, with a medianage of 41 years; 55.8 percent were females; 56.8 percent had a four-year college degree

Consumertraits and

demographics

51


or higher education; 62 percent responded that their annual household income wasabove $50,000; 86.3 percent were Caucasian; and 59.3 percent were married.

MeasurementRespondents’ demographic information including gender, age, income, and educationwas measured. Respondents indicated their gender and gender was noted as adichotomous variable (0 – male and 1 – female). Age was measured by askingrespondents’ year of birth and subtracting it from the year of data-collection. Incomewas measured by eight household income categories in $10,000 increments andeducation was measured by five education categories (high school or less, associatedegree, bachelor’s degree, master’s degree, and doctoral degree).

Scale items for technology anxiety were borrowed from Meuter et al. (2003); need forinteraction, from Dabholkar (1996); and technology innovativeness, from Bruner andKumar (2007). To measure intention to use self-checkouts, scale items were adaptedfrom Nysveen et al. (2005). With the exception of demographic measures, all items inthe questionnaire were measured on a seven-point scale ranging from “stronglydisagree” to “strongly agree.”

ResultsMeasurement modelThe quality of the measurement model was assessed through confirmatory factoranalysis using maximum-likelihood method. The estimation of the measurementmodel generated a good fit: x 2(143) ¼ 336.72, p , 0.001; x 2/df ¼ 2.36; CFI ¼ 0.94;TLI ¼ 0.93; RMSEA ¼ 0.069. As reported in Table I, the t-values for the loadings

Latent variablesManifestvariables

Standardizedestimate t-value

Compositereliability

Averagevarianceextracted

Technology anxiety TA01 0.78 15.11 * 0.91 0.55TA02 0.75 14.43 *

TA03 0.62 11.09 *

TA04 0.60 10.70 *

TA05 0.68 12.56 *

TA06 0.82 16.68 *

TA07 0.82 16.53 *

TA08 0.81 16.48 *

Need for interaction NI01 0.69 12.09 * 0.80 0.50NI02 0.64 11.05 *

NI03 0.61 19.78 *

NI04 0.86 15.97 *

Technology innovativeness TI01 0.82 16.43 * 0.93 0.72TI02 0.88 18.44 *

TI03 0.86 17.94 *

TI04 0.79 15.84 *

TI05 0.90 19.21 *

Intention to use retail self-checkouts INTENT01 0.81 16.65 * 0.90 0.83INTENT02 0.99 23.78 *

Notes: Significance at: *p , 0.001; n ¼ 285

Table I.Measurement modelresults

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ranged from 10.70 to 23.78, demonstrating adequate convergent validity. In addition,the composite reliability for each construct exceeded the acceptable level of 0.70 andthe average variance extracted (AVE) for each construct accounted for more than 0.50of the total variance (Fornell and Larcker, 1981). These findings indicate that scaleitems for four latent constructs were reliable and valid measures. Discriminant validityamong four latent constructs was also proven because the squared correlationsbetween all possible pairs of the latent construct were smaller than the AVE for theunderlying construct (Fornell and Larcker, 1981).

Structural model and hypotheses testingStructural equation modeling was used to estimate parameters of the structural model.Goodness-of-fit statistics of the structural model were acceptable: x 2(207) ¼ 495.96,p , 0.001; x 2/df ¼ 2.39; CFI ¼ 0.92; TLI ¼ 0.90; RMSEA ¼ 0.070. Results of hypothesestesting are summarized in Table II. H1a tests whether women have stronger technologyanxiety than men. The results show that this path coefficient is positive and significant(0.14, p , 0.05), indicating that technology anxiety is greater for women than men. H1bposits that women consider interaction with a store employee more important than men.However, such effect is not significant for need for interaction (20.09, p ¼ 0.15). H1c issupported by the significant negative path coefficient (0.18, p , 0.01), indicating that menare more technologically innovative than women.

H2a-H2c propose that age is positively related to technology anxiety and need forinteraction whereas age is negatively related to technology innovativeness. Resultsindicate that all of these path coefficients are significant in the hypothesized direction(technology anxiety: 0.22, p , 0.001; need for interaction: 0.18, p , 0.01; andtechnology innovativeness: 20.18, p , 0.01). These findings suggest that olderconsumers tend to have greater technology anxiety, need more interaction with a storeemployee, and are less-technologically innovative, compared to younger consumers.

Hypothesis Structural path Standardized estimate t-value

H1a Gender ! technology anxiety 0.14 2.36 *

H1b Gender ! need for interaction 20.09 21.44H1c Gender ! technology innovativeness 20.18 23.01 * *

H2a Age ! technology anxiety 0.22 3.59 * * *

H2b Age ! need for interaction 0.18 2.79 * *

H2c Age ! Technology innovativeness 20.18 23.03 * *

H3a Education ! technology anxiety 20.08 21.21H3b Education ! technology innovativeness 20.03 20.45H4a Income ! technology anxiety 20.16 22.44 *

H4b Income ! technology innovativeness 0.03 0.39H5a Gender ! intention to use 0.00 20.00H5b Age ! intention to use 0.01 0.18H5c Education ! intention to use 0.01 0.94H5d Income ! intention to use 0.06 0.08H6a Technology anxiety ! intention to use 20.12 21.98 *

H6b Need for interaction ! intention to use 20.25 23.88 * * *

H6c Technology innovativeness ! intention to use 0.25 4.14 * * *

Note: Significant at: *p , 0.05, * *p , 0.01 and * * *p , 0.001, respectively

Table II.Results of the structural

equation model

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The path coefficients from education to technology anxiety and technologyinnovativeness are not significant, rejecting H3a and H3b. H4a is supported by thesignificant negative path coefficient (20.16, p , 0.05), indicating that technologyanxiety decreases, as income level increases. However, such effect is not significant fortechnology innovativeness, not supporting H4b.

H5a-H5d test the direct impact of demographic factors (i.e. gender, age, education,and income) on intention to use retail self-checkouts. Results show that none of thesepath coefficients are significant at the 0.05 level, suggesting that demographic factorsdo not directly influence intention to use retail self-checkouts.

H6a-H6c test whether technology anxiety, need for interaction, and technologyinnovativeness significantly influence intention to use retail self-checkouts. Therelationships of technology anxiety (20.12, p , 0.05) and need for interaction (20.25,p , 0.001) to intention to use retail self-checkouts are negative and significant whereasthe relationship of technology innovativeness (0.25, p , 0.001) to intention to use retailself-checkouts is positive and significant.

DiscussionsBy first classifying individual difference traits into demographic factors and consumertraits, this study empirically explores the relationships among demographic factors(gender, age, education, and income), consumer traits (technology anxiety, need forinteraction, and technology innovativeness), and intention to use retail self-checkouts.Furthermore, our interest lies in identifying whether demographic factors directly orindirectly influence intention to use retail self-checkouts. The results of this studydemonstrate that demographic factors (i.e. gender, age, and income) only indirectlyinfluence intention to use retail self-checkouts through consumer traits. That is,consumers’ different personality traits arising from demographic factors introducevariability in their intention to use retail self-checkouts. Therefore, understanding howeach demographic factor relates to consumers’ personal traits could assist retailers whoattempt to segment consumers in the SST encounters. Based on the findings from thisstudy, instead of simply implementing market segmentation by demographic factors,retailers should be aware of the underlying relationship between demographic factorsand consumer traits. For example, because men and women differ in terms oftechnology anxiety, they show differences in their intention to use retail self-checkouts.This study provides the reason why different people are not similar in the use of retailself-checkouts and concludes that this difference can be attributed to consumer traitswhich are determined by some of the demographic factors.

Our results indicate that gender significantly influences intention to use retailself-checkouts through technology anxiety and technology innovativeness. Asexpected, women tend to exhibit a greater level of technology anxiety while men aremore likely to be innovative toward technology. In this study, there is no difference inthe extent of need for interaction between men and women. Accordingly, this genderdifference originating from technology anxiety and technology innovativenesssignificantly influences intention to use retail self-checkouts.

Our results show that age has a significant influence on intention to use retailself-checkouts in combination with technology anxiety, need for interaction, andtechnology innovativeness. That is, older consumers who tend to have moretechnology anxiety are less likely to use retail self-checkouts than younger consumers

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with less-technology anxiety. Our results also support that age is positively related toneed for interaction, which in turn is negatively associated with intention to use retailself-checkouts. This finding is consistent with previous studies arguing that olderpeople seek personal interaction in shopping environments and prefer personalassistance over self-service (Dean, 2008; Simon and Usunier, 2007). In addition,younger consumers who tend to be more technologically innovative are more likely touse retail self-checkouts than older consumers with less-technology innovativeness.It would be important for younger consumers to be the first to adopt retailself-checkouts before most others know the existence of them.

In our study, education is shown to have no direct and indirect effect on intention touse retail self-checkouts. Therefore, individual differences in technology anxiety andtechnology innovativeness cannot be explained by the level of educational attainment.Thus, retailers should not use education as important demographic information tosegment their consumers in the context of retail self-checkouts. Finally, the resultsshow that income only indirectly influences intention to use retail self-checkoutsthrough technology anxiety. That is, consumers with a higher income tend to exhibitlower technology anxiety, which in turn results in greater intention to use retailself-checkouts. On the other hand, no difference was found in technologyinnovativeness between high and low-income consumers. This finding indicates thatconsumers with a higher income do not necessarily have a strong tendency to adoptretail self-checkouts. Retail self-checkouts may not be considered as new technology forconsumers with a high income.

Managerial implicationsSince our results find the negative relationship between technology anxiety and intentionto use retail self-checkouts, retailers should make an attempt to decrease technologyanxiety when they particularly target women, older consumers, and consumers with a lowincome. First, training programs could be suggested to assist the consumers. Trainingprograms help consumers perceive using retail self-checkouts as comfortable as theprograms allow consumers to overcome psychological barriers to use such SST (Agarwaland Prasad, 1999). In addition, store employees should provide personal assistance forhelping this group of consumers to learn how to use retail self-checkouts. Offeringcustomer-friendly detailed instructions (e.g. voice instruction) could be also effective whena contact employee is not available. Second, retail self-checkouts should be designed to beeasily understood and operated for those consumers. Easy-designed self-checkouts willhelp increase their intention to use retail self-checkouts.

Based on our findings related to older consumers’ greater need for interaction,which negatively influence intention to use retail self-checkouts, retailers could avoidinstalling retail self-checkouts in stores where older consumers are the dominantpopulation. With respect to the relationship of technology innovativeness to intentionto use retail self-checkouts, when retailers’ primary target group is young maleconsumers (e.g. best buy), they could focus on their innovative predisposition towardtechnology. To encourage young male consumers to use retail self-checkouts, retailersneed to emphasize the newness of retail self-checkouts. Retailers could also provide anincentive that could be saving time without waiting for a long checkout line or savingmoney if providing consumers loyalty points to get discount coupons. Theabove-suggested recommendations will not only contribute to an increase in the use

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of retail self-checkouts but also lead to favorable reactions to retail self-checkouts,which create positive word-of-mouth (Meuter et al., 2003).

Limitations and suggestions for future researchSince we limited the discussion to the effects of individual difference traits on theadoption of retail self-checkouts, we only included demographic factors and consumertraits as determinants of intention to use retail self-checkouts. However, self-checkoutdesign and interface features (e.g. service complexity) or situational factors (e.g.waiting time) may be better predictors in determining the use of retail self-checkouts.Therefore, future research could attempt to draw a comprehensive picture of retailself-checkouts by incorporating other relevant factors. Caution needs to be exercised tointerpret the results of this study due to the limitation of sampling. As we used anonline survey utilizing a consumer panel, the sample characteristics may not reflect thetrue consumers’ characteristics. For example, our sample may exhibit a lower level ofinternet phobia, compared to the entire consumer population. Future research mayadopt other data-collection methods such as mall intercept surveys or personalinterviews.

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Corresponding authorHyun-Joo Lee can be contacted at: [email protected]

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